A comparison of trust metrics on the Advogato social network

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Check the paper at http://www.gnuband.org/papers/a_comparison_of_trust_metrics_on_advogato_social_network/


A comparison of trust metrics on Advogato social network

Contents

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Abstract

In this paper we propose a comparison of different trust metrics previously proposed in literature on the real world dataset of Advogato, a community of free software developers. and its peculiar characteristics is trust statements/relationships are weighted.

Introduction

we ...

intro about how it is common to interact with unknown people/entities and how it is important to have tools for getting an (initial) idea of the trustworthiness of the other party.... trust metrics / reputation systems

In motivation cite Artificial Intelligence Review (2005) Review on Computational Trust and Reputation Models JORDI SABATER & CARLES SIERRA: Finally, analyzing the models presented in this article we found that there is a complete absence of test-beds and frameworks to evaluate and compare the models under a set of representative and common conditions. This situation is quite confusing, specially for the possible users of these trust and reputation models. It is thus urgent to define a set of test-beds that allow the research community to establish comparisons in a similar way to what happens in other areas (e.g. machine learning (UCI 2003)).

Mention there is ART Testbed, cite "A Design Foundation for a Trust-Modeling Experimental Testbed" but say how this is different: it is more about strategies for interactions in societies, in which there is competition.


Our contributions are: (it is important to clearly state what you think are the contributions we are bringing to world/science/someone)

  • Analyzing dataset (peculiarity: weighted, directed, real world). [it is the first on a directed weighted network? Check! Most of the studies are based on undirected, unweighted networks (add example and cite Newman paper or something else).
  • Comparing different trust metrics.
  • propose/define ways to compare them. There are no evaluation of trust metrics bla bla bla, this paper starts to fill this gap, the collaborative environment trustlet.org with code and dataset hope to aggregate enough researchers, ... community, dedicated to this challenge...

Advogato social network

Advogato [1] is an online community site dedicated to free software development, launched in November 1999. It was created by Raph Levien, who also used Advogato as a research testbed for testing his own attack-resistant trust metric, the Advogato trust metric. On Advogato users can certify each other on three different levels: Apprentice, Journeyer, and Master and the Advogato trust metric uses this information in order to assign a certification level to every user. The goal is to be attack-resistant, i.e. to reduce the impact of attackers.

An interesting characteristic of the Advogato dataset is that is it weighted: directed edges between nodes are specified on a 4 levels base, Observer, Apprentice, Journeyer, and Master. These are defined as such: Masters are supposed to be principal authors of an "important" free software project, excellent programmers who work full time on free software, Journeyers contribute significantly, but not necessarily full-time, Apprentices contribute in some way, but are still acquiring skills to make more significant contributions. Observers are users without trust certification, which is also the default. It is also the level you certify someone to remove an existing trust certification.

However it might be argued that not necessarily all the users checked, were aware of and followed the suggested semantics.

For the purpose of this paper we consider these certifications as trust statements. T(A,B) donotes the certification (trust statement) expressed by user A about user B and we map the textual labels Observer, Apprentice, Journeyer and Master in the range [0,1], respectively in the values 0.4, 0.6, 0.8 and 1.0. This choice is somehow arbitrary but it considers the fact all the certifications are positive judgments, except for "observer" which is often used for expressing less-than-sufficient levels. For example we model the fact raph certified federico as Journeyer as T(raph,federico)=0.8.

There are other web communities using the same software powering Advogato.org and they have the same social structure: same trust levels and certifications system. These communities are robots.net, persone.softwarelibero.org, people.squeakfoundation.org, kaitiaki.org.nz. The software publishes the entire trust graph as a graph.dot file in the dot format.

Trust metrics

A trust metric is a technique for predicting how much a certain user can be trusted by the other users of the community [2].

The basic assumption of trust metrics is that trust can be propagated in some way. The reason is that you trust your friend more than a stranger and so, under certain conditions, a friend of your friend is possibly more trustworthy than a random stranger (at least because your friend trusts her).

For example, in the context of cinema, if all your 10 trusted cinema friends trust "Mary" (who you don't know) about her taste in movies, a trust metric might predict that you will find her opinion about movies useful as well and so that you could trust her opinion.

In decentralized environments, in which there are many autonomous entities (users, robots, servers, peers, ...) and it is quite common to interact with unknown entities, it is important to have some tools for making informed guesses about the trustworthiness of these other entities. Trust metrics have in fact been applied to domains as different as social web sites, P2P systems, recommender systems, mobile computing, public key cryptography ...

Trust metrics can either be local or global, depending on the fact they compute personalized values of trust or not[3]. Attack-resistance also is an important property but we don't analyze it here.

Recently there have been many proposals of trust metrics but a deep evaluation of different trust metrics on different realistic datasets is still missing. This is mainly because it's hard to get real world data and so most of the proposed trust metrics are simply not evaluated and surely never compared.

Our contribution with this paper tries to fill this important gap for the research community. We in fact compare different trust metrics on some real world datasets.

Both providing code (Python) and datasets

TODO: write one paragraph for explaining each trust metric

One of the most trivial trust metrics is simple unpersonalized average which is used by Ebay, t(a, b) = Sigma(in_trust_b), simple example.

The Advogato trust metric is one of the first proposed trust metrics. It was created by Raph Levien, with the goal to make it attack-resistant. It is described here. It is based on the netflow algorithm. If the flow, which starts from 4 seeds in case of the global Advogato trust metric, reaches a node it is considered certified. In our localized version we let the flow start from the point of view of the truster. The flow is first calculated for edges with the master certification to find Masters, and then for both Journeyer and Master, and finally Master, Journeyer and Apprentice edges.

We used a version of PageRank that handles weighted links and rescaled the resulting values.

  • moletrust (the simple breadth-first one Paolo proposed)

In case a trust metric is not discrete we also compared the thresholded version, where values are rounded off, e.g. 0.95 becomes 1.0 (Master).

    • need for local trust metric? AdvogatoLocal? From Levien thesis: Trust “seed” is hard-wired. In practice, hard-wired seed hasn’t caused problems, but it is a concern. Providing user-configured alternate seeds is a possible extension, but the need for it hasn’t been strongly felt.


  • some trivial ones, for example the trust metric that predicts always "master" (everyone_master) or journeyer (called everyone_journeyer) or ...
  • shall we use some other ones (see)? Probably not for this paper.
    • (we can remove this from this paper) There is probably a lot of reciprocation in the network, so an effective metric might increase the trust score when trust statements are not balanced. That is, if I go around and I certify everyone in the network there is high probability they will certify me back so getting high indegree is easy. So an unbalanced certification is very informative and useful, i.e. I certify rms as guru but rms does not certify me because he does not know me ... need to think better about this but wanted to write it down here. --PaoloMassa 10:41, 11 September 2007 (PDT)

Trust metrics evaluation methodology

We compared these trust metrics using the leave-one-out technique, which is common in machine learning.

The process is as follows: One trust edge (e.g. from node A to node B) is deleted from the graph and then the trust metric is used to predict the trust value A should place in B, i.e. the missing edge. We repeat this for all edges to obtain a prediction graph, in which some edges can contain an undefined trust value. The real and the predicted values are compared in several ways: the coverage, which is a measure of the edges that were able to be predicted, the absolute error, the root mean square error and in case of discrete trust metrics the ratio of correctly predicted edges.

The real value and the predicted value are then compared to compute a measure of error on this single prediction step. It is also possible that a trust metric is not able to compute the trust value and this refers to the coverage of the trust metric.

This evaluation step is repeated for all the edges and a global measure of error is computed, for example by averaging all the single errors and the coverage or by doing more deep analysis by considering only edges that satisfy certain constraints, for example, only on edges into nodes with a lot of friends, only into journeyer node or only for "master" edges, etc.

TODO: analyze deeply the results to see what can be said

We don't take the approach of diving users in good users and bad users. We think it is not the correct approach in social settings (cite controblablabla). For instance there is an user, whose nick is "rms", which is not Richard M. Stallman, but still it is certified as Master by a lot of users (363 users of which 321 as Master, it is the forth most certified user, after 3 of the 4 founders!). From an attack point of view, this user could be considered an attacker since it is social engineering its reputation (in this case simply by choosing a certain nick) and then possibly profiting from this.

Experimental results

underline that the code and the datasets are available under meaningful license at trustlet.org!!!


First there will be an analysis of the social network of Advogato: how many Master edges, how many Apprentice, ..., it is power law? Which exponent? It is connected? and much more, see also for inspiration The structure and function of complex networks

Dataset analysis

The Advogato dataset that was analyzed is a directed, weighted graph with 7294 nodes and 52981 trust relations. The dataset is comprised of 1 large connected component, followed by components of size 7 and smaller. Since we can not say anything sensible about components of size 1 and 2 we decided to leave these out of our analysis. 70.5% nodes are in the largest component. The second largest component contains 7 nodes.

The mean indegree (number of incoming edges per user) is 7.26. (the outdegree is obviously the same, since edges going in some node came out of some node).

The standard deviation of the number of incoming nodes is 20.91 and of the outgoing nodes is 21.75.

How many users (and in percentage) received 0 incoming edges? 1? 2? ...

Outdegree (0, 3248), (1, 943), (2, 437), (3, 330), (4, 255), (5, 213), (6, 158), (7, 163), (8, 152), (9, 100), (10, 101), (11, 77), (12, 70), (13, 62), (14, 51), (15, 48), (16, 43), (17, 31), (18, 43), (19, 32), (20, 34), (21, 35), (22, 31), (23, 34), (24, 25), (25, 30), (26, 21), (27, 23), (28, 23), (29, 22), (30, 15), (31, 17), (32, 16), (33, 15), (34, 10), (35, 14), (36, 23), (37, 10), (38, 10), (39, 8)

Indegree distribution

(0, 2686), (1, 1160), (2, 553), (3, 403), (4, 308), (5, 194), (6, 190), (7, 154), (8, 143), (9, 131), (10, 98), (11, 113), (12, 79), (13, 67), (14, 56), (15, 65), (16, 52), (17, 52), (18, 45), (19, 47), (20, 31), (21, 31), (22, 33), (23, 30), (24, 30), (25, 18), (26, 28), (27, 20), (28, 17), (29, 18), (30, 21), (31, 22), (32, 16), (33, 13), (34, 16), (35, 16), (36, 16), (37, 14), (38, 14), (39, 16)

From previous table, we can see the Advogato trust network indegree obeys the power law distribution (how to find exponent?). COMPLETE THIS! (what about the trust network only considering Master edges? Only Journeyer? ...) COMPLETE THIS!

The mean shortest path length is 3.75.

The average cluster coefficient is 0.116.

About the values of trust on edges: what is the distribution? How many Master edges, Apprentice, Observer, Journeyer? There are 17489 Master judgments, 21977 for Journeyer, 8817 for Apprentice and 4698 for Observers.

What is the number of users who received only one kind of trust values? For example, users who were judged only as "master" by everyone, or only as "apprentice", .... (These users are not at all controversial, all the community agree about them and so they are not hard to predict). The same question but limiting to users with 5 or more incoming trust edges. There are 4607 users who have received only one kind of trust value. There are 183 users with 5 or more trust edges that all have the same value.


The reciprocity is 0.33 (one third of the trust judgments are reciprocated). It is actually surprising small. Argument that in professional networks (linkedin) you need to keep the relationships accurate so you are not going to reciprocate every received statement (especially from unknown users) while in entertainment networks (facebook or friendster) everybody tend to reciprocate every incoming friendship since there is no incentive in turning them down. Evidently Advogato is more like a professional network in which users state their real relationships and also tend to not reciprocate all the judgmenebts (also because some are coming from unknown users)

(we could even think about an analysis of reciprocation in different networks (flickr, del.icio.us, last.fm, epinions, facebook, coucsurfing...)

Also it would be interesting to understand: how many of the reciprocated edges are reciprocated with the same value? I.e.: If I say you are Master, do you say I'm Master...

In [114]: map(lambda x: scipy.average([(A.trust_on_edge(e) - _trust_val(A, e[1], e[0])) for e in A.edges_iter() if A.has_edge(e[1], e[0]) and A.trust_on_edge(e) == x]), [0.4, 0.6, 0.8, 1.0]) Out[114]: [-0.284233261339, -0.128773841962, 0.0145418976198, 0.15511466117] As a summary of the previous table, we computed the average difference between the given certification and the received certificate in the reciprocated certificates for different values of certification.

Observer: -0.284233261339 Journeyer: -0.128773841962 Apprentice: 0.0145418976198 Master: 0.15511466117

M J A O
M 1646 1594 507 134
J 1594 5678 1595 334
A 507 1595 1322 246
O 134 334 246 212


M J A O
M 42.41% 41.07% 13.06% 3.45%
J 17.32% 61.71% 17.34% 3.63%
A 13.81% 43.46% 36.02% 6.70%
O 14.47% 36.07% 26.57% 22.89%
  • Analyze cohesion in the social network, how many people certify each other? Density Degree of nodes (number of incoming links, how many users have 2 incoming links, how many 5, ... and is this a power law?) Components Cores ... --PaoloMassa 10:32, 11 September 2007 (PDT)
  • Interesting will be also maybe to analyze the controversiality of users (a user is not controversial if all the other users express the same judgement about her (i.e. all of the judger think she is a Master), a user is controversial if other users express different judgements about her (4 think she is Master, 4 think she is Apprentice, 4 thinks she is Journeyer ...). see Trust metrics on controversial users: balancing between tyranny of the majority and echo chambers. We could even define a Controversiality index, both for the single user and for the community in its entirety. --PaoloMassa 10:28, 11 September 2007 (PDT)
  • Triads and missing relationships. --PaoloMassa 10:28, 11 September 2007 (PDT)
  • Place a cool visualization of the network? It is not very informative but it is in general attractive --PaoloMassa 10:35, 11 September 2007 (PDT)

Trust metrics evaluation

Then there will be a comparison of the different trust metrics on the dataset, also focusing on particular views (popular users, not very postitive edges, ...)

Important point made by Kasper: advogato is a "discrete" trust metric... and all the others are continuous. We need to compare them in comparable situations.

Be frank about the intention behind the creation of the tested trust metrics.

  • Pagerank was created for producing a global ranking of pages in order to discover the good ones and the less interesting ones, not for predicting the value of an edge (moreover on the web edges don't have values).
  • Advogato was created with the goal of being attack-resistant in the sense to not give a high certificate to the few users who are malicious. Note that the underlying assumption if that most users are in good faith and there are just few malicious nodes. For this reason it tends to "get in" with everyone that is reached by the trust propagation (max flow). In fact theorem 1 if advogato trust metric clearly speaks about bounds in the number of bad nodes that get certified as good: "the number of bad nodes chosen is equal to the total flow minus the number of good and confused nodes chosen".Just as PageRank, Advogato was not created for inferring the correct value of trust that might be there between user A and user B. "Advogato’s attack model partitions nodes into three types: Good nodes behave well and have not certified any bad nodes. Confused nodes behave well but have issued certifications to bad nodes.•Bad nodes are under the control of the attacker. The attacker controls who they certify and what they do."

(It is important to mention these points, because the intention behind an algorithm are of course decisive in its design and performance in different situations).

Conclusions

References

Place them around in the text ...

About evaluating trust metrics [4]

Comparing Advogato and Pagerank [5]

About evaluating trust metric, Trust Metrics on Controversial Users: Balancing Between Tyranny of the Majority and Echo Chambers [3]

  1. http://advogato.org
  2. add references
  3. 3.0 3.1 Massa, P.; Avesani, P. (2007). "Trust Metrics on Controversial Users: Balancing Between Tyranny of the Majority and Echo Chambers (link to the full paper in PDF)". INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS 3 (1): 39. 
  4. Golbeck, J.; Hendler, J. (2004). "Accuracy of metrics for inferring trust and reputation in semantic web-based social networks (link to the full paper in PDF)". Proceedings of EKAW 4. Retrieved on 2007-08-27. 
  5. A comparison of two trust metrics [1]
  • D. Quercia, S. Hailes, and L. Capra. Lightweight Distributed Trust Propagation. In Proceedings of the 7th IEEE International Conference on Data Mining
    • uses advogato dataset
  • Modeling and Evaluating Trust Network Inference by Li Ding Pranam Kolari Shashidhara Ganjugunte Tim Finin Anupam Joshi / Seventh International Workshop on Trust in Agent Societies at AAMAS 2004
    • propose a new framework.


  • Trust Modeling and Evaluation for Ad Hoc Networks?
  • Trust No One: Evaluating Trust-based Filtering for Recommenders?
  • Towards a Gravity-Based Trust Model for Social Networking Systems Maheswaran, Muthucumaru; Tang, Hon Cheong; Ghunaim, Ahmad ?

Tables

coverage_cond                   |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|master              |observer            |journeyer           |apprentice
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon4_threshold05|0.954606            |0.979699            |0.980916            |0.981650            |0.981684            |0.967923            |0.931460            |0.963598            |0.918113
OutB_TM                         |0.921727            |0.949704            |0.962701            |0.960844            |0.956423            |0.924124            |0.863346            |0.949493            |0.878870
AlwaysMaster                    |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000
AlwaysApprentice                |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000
AlwaysJourneyer                 |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000
PageRankGlobalTM                |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000
MoletrustTM_horizon3_threshold05|0.931107            |0.963459            |0.971136            |0.974781            |0.976445            |0.954200            |0.915070            |0.936980            |0.879211
MoletrustTM_horizon4_threshold0 |0.954606            |0.979699            |0.980916            |0.981650            |0.981684            |0.967923            |0.931460            |0.963598            |0.918113
MoletrustTM_horizon3_threshold0 |0.931107            |0.963459            |0.971136            |0.974781            |0.976445            |0.954200            |0.915070            |0.936980            |0.879211
MoletrustTM_horizon2_threshold05|0.795512            |0.836392            |0.870048            |0.890563            |0.903099            |0.856253            |0.773308            |0.796879            |0.683452
EbayTM                          |0.978105            |1.000000            |1.000000            |1.000000            |1.000000            |0.994968            |0.945509            |0.985303            |0.944085
OutA_TM                         |0.982201            |0.984277            |0.984659            |0.985001            |0.985014            |0.977300            |0.986164            |0.984484            |0.984122
EdgesA_TM                       |0.992941            |0.994200            |0.994359            |0.994293            |0.993989            |0.989365            |0.991486            |0.995586            |0.994216
AlwaysObserver                  |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000
RandomTM                        |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000
MoletrustTM_horizon2_threshold0 |0.795512            |0.836392            |0.870048            |0.890563            |0.903099            |0.856253            |0.773308            |0.796879            |0.683452
EdgesB_TM                       |0.986674            |1.000000            |1.000000            |1.000000            |1.000000            |0.997484            |0.957642            |0.992674            |0.965748



abs_error_cond                  |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|master              |observer            |journeyer           |apprentice          
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon4_threshold05|0.105855 50576      |0.105136 47294      |0.105755 37213      |0.106807 29583      |0.107005 24172      |0.105592 16928      |0.346449 4376       |0.066314 21177      |0.079787 8095       
OutB_TM                         |0.145317 48834      |0.143399 45846      |0.142496 36522      |0.145550 28956      |0.149375 23550      |0.158141 16162      |0.376720 4056       |0.073784 20867      |0.190078 7749       
AlwaysMaster                    |0.202733 52981      |0.190231 48274      |0.169017 37937      |0.152940 30136      |0.140145 24623      |0.000000 17489      |0.600000 4698       |0.200000 21977      |0.400000 8817       
AlwaysApprentice                |0.232736 52981      |0.242615 48274      |0.262425 37937      |0.278186 30136      |0.290509 24623      |0.400000 17489      |0.200000 4698       |0.200000 21977      |0.000000 8817       
AlwaysJourneyer                 |0.134773 52981      |0.132005 48274      |0.134671 37937      |0.140370 30136      |0.145433 24623      |0.200000 17489      |0.400000 4698       |0.000000 21977      |0.200000 8817       
PageRankGlobalTM                |0.156153 52981      |0.149971 48274      |0.136356 37937      |0.127701 30136      |0.122127 24623      |0.172963 17489      |0.280490 4698       |0.136331 21977      |0.105965 8817       
MoletrustTM_horizon3_threshold05|0.105555 49331      |0.104997 46510      |0.105734 36842      |0.106825 29376      |0.107006 24043      |0.104539 16688      |0.348230 4299       |0.065386 20592      |0.079864 7752       
MoletrustTM_horizon4_threshold0 |0.103064 50576      |0.103191 47294      |0.104452 37213      |0.105948 29583      |0.106430 24172      |0.104814 16928      |0.331179 4376       |0.064874 21177      |0.075994 8095       
MoletrustTM_horizon3_threshold0 |0.102889 49331      |0.103128 46510      |0.104465 36842      |0.106006 29376      |0.106465 24043      |0.103799 16688      |0.332926 4299       |0.064213 20592      |0.076093 7752       
MoletrustTM_horizon2_threshold05|0.103849 42147      |0.103810 40376      |0.105046 33007      |0.106186 26838      |0.106129 22237      |0.100061 14975      |0.357826 3633       |0.062913 17513      |0.079116 6026       
EbayTM                          |0.101082 51821      |0.101018 48274      |0.101599 37937      |0.102984 30136      |0.103240 24623      |0.097703 17401      |0.349662 4442       |0.060934 21654      |0.079932 8324       
OutA_TM                         |0.113828 52038      |0.111805 47515      |0.112012 37355      |0.114091 29684      |0.116719 24254      |0.141218 17092      |0.161010 4633       |0.059326 21636      |0.170581 8677       
EdgesA_TM                       |0.123219 52607      |0.121889 47994      |0.123593 37723      |0.127345 29964      |0.131482 24475      |0.162913 17303      |0.218759 4658       |0.057593 21880      |0.157903 8766       
AlwaysObserver                  |0.397267 52981      |0.409769 48274      |0.430983 37937      |0.447060 30136      |0.459855 24623      |0.600000 17489      |0.000000 4698       |0.400000 21977      |0.200000 8817       
RandomTM                        |0.223114 52981      |0.225463 48274      |0.232662 37937      |0.239781 30136      |0.245610 24623      |0.301687 17489      |0.303674 4698       |0.166031 21977      |0.166619 8817       
MoletrustTM_horizon2_threshold0 |0.101672 42147      |0.102273 40376      |0.104071 33007      |0.105689 26838      |0.106014 22237      |0.099849 14975      |0.344370 3633       |0.061809 17513      |0.075732 6026       
EdgesB_TM                       |0.113275 52275      |0.111711 48274      |0.111630 37937      |0.113530 30136      |0.114407 24623      |0.112511 17445      |0.363901 4499       |0.056882 21816      |0.126902 8515       

Ebay is the best metric, according to previous table. But we need to evaluate trust metrics on more challenging views (such as controversial users). So there is the next table. But unfortunately in the next table we forgot to evaluate some trust metrics (Ebay for instance), but now the tests are running and the next table will be updated.

coverage_cond                   |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|master              |observer            |journeyer           |apprentice
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon4_threshold05|0.954606            |0.979699            |0.980916            |0.981650            |0.981684            |0.980721            |0.970767            |0                   |0                   |0                   |0.980229            |0.973399            |0                   |0                   |0                   |0.979778            |0.972390            |0                   |0                   |0                   |0.967923            |0.931460            |0.963598            |0.918113
OutB_TM                         |0.921727            |0.949704            |0.962701            |0.960844            |0.956423            |0.960568            |0.847747            |0                   |0                   |0                   |0.957585            |0.859606            |0                   |0                   |0                   |0.953290            |0.853322            |0                   |0                   |0                   |0.924124            |0.863346            |0.949493            |0.878870
AlwaysMaster                    |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |1.000000            |1.000000
AlwaysApprentice                |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |1.000000            |1.000000
AlwaysJourneyer                 |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |1.000000            |1.000000
PageRankGlobalTM                |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |0                   |0                   |0                   |1.000000            |1.000000            |0               

abs_error_cond                  |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|master              |observer            |journeyer           |apprentice
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon4_threshold05|0.105855 50576      |0.105136 47294      |0.105755 37213      |0.106807 29583      |0.107005 24172      |0.113416 29199      |0.197327 1594       |0                   |0                   |0                   |0.115720 34804      |0.199266 1976       |0                   |0                   |0                   |0.118158 37211      |0.203691 2254       |0                   |0                   |0                   |0.105592 16928      |0.346449 4376       |0.066314 21177      |0.079787 8095
OutB_TM                         |0.145317 48834      |0.143399 45846      |0.142496 36522      |0.145550 28956      |0.149375 23550      |0.150180 28599      |0.233416 1392       |0                   |0                   |0                   |0.150002 34000      |0.224609 1745       |0                   |0                   |0                   |0.151336 36205      |0.223698 1978       |0                   |0                   |0                   |0.158141 16162      |0.376720 4056       |0.073784 20867      |0.190078 7749
AlwaysMaster                    |0.202733 52981      |0.190231 48274      |0.169017 37937      |0.152940 30136      |0.140145 24623      |0.156995 29773      |0.177710 1642       |0                   |0                   |0                   |0.172985 35506      |0.186207 2030       |0                   |0                   |0                   |0.180347 37979      |0.190768 2318       |0                   |0                   |0                   |0.000000 17489      |0.600000 4698       |0.200000 21977      |0.400000 8817
AlwaysApprentice                |0.232736 52981      |0.242615 48274      |0.262425 37937      |0.278186 30136      |0.290509 24623      |0.276217 29773      |0.302923 1642       |0                   |0                   |0                   |0.262446 35506      |0.296355 2030       |0                   |0                   |0                   |0.257200 37979      |0.293788 2318       |0                   |0                   |0                   |0.400000 17489      |0.200000 4698       |0.200000 21977      |0.000000 8817
AlwaysJourneyer                 |0.134773 52981      |0.132005 48274      |0.134671 37937      |0.140370 30136      |0.145433 24623      |0.143472 29773      |0.204507 1642       |0                   |0                   |0                   |0.140630 35506      |0.201576 2030       |0                   |0                   |0                   |0.140499 37979      |0.201812 2318       |0                   |0                   |0                   |0.200000 17489      |0.400000 4698       |0.000000 21977      |0.200000 8817
PageRankGlobalTM                |0.156153 52981      |0.149971 48274      |0.136356 37937      |0.127701 30136      |0.122127 24623      |0.132599 29773      |0.194611 1642       |0                   |0                   |0                   |0.141560 35506      |0.208965 2030       |0                   |0                   |0                   |0.146602 37979      |0.219483 2318       |0                   |0                   |0                   |0.172963 17489      |0.280490 4698       |0.136331
abs_error_cond                  |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|master              |observer            |journeyer           |apprentice          
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
EbayTM                          |0.101082 51821      |0.101018 48274      |0.101599 37937      |0.102984 30136      |0.103240 24623      |0.104577 32755      |0.109222 29773      |0.135227 13075      |0.189849 1642       |0.104640 41307      |0.111294 35506      |0.138239 15271      |0.192179 2030       |0.265682 254        |0.105931 45926      |0.113743 37979      |0.141325 16513      |0.196911 2318       |0.272450 322        |0.097703 17401      |0.349662 4442       |0.060934 21654      |0.079932 8324       
MoletrustTM_horizon2_threshold0 |0.101672 42147      |0.102273 40376      |0.104071 33007      |0.105689 26838      |0.106014 22237      |0.107406 28869      |0.112027 26256      |0.139111 11404      |0.195939 1404       |0.106729 35344      |0.113488 30583      |0.141206 13005      |0.198012 1679       |0.261568 206        |0.106977 38516      |0.114797 32280      |0.142692 13846      |0.199662 1866       |0.273351 242        |0.099849 14975      |0.344370 3633       |0.061809 17513      |0.075732 6026       

coverage_cond                   |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|master              |observer            |journeyer           |apprentice          
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
EbayTM                          |0.978105            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |0.994968            |0.945509            |0.985303            |0.944085            
MoletrustTM_horizon2_threshold0 |0.795512            |0.836392            |0.870048            |0.890563            |0.903099            |0.881362            |0.881873            |0.872199            |0.855055            |0.855642            |0.861347            |0.851614            |0.827094            |0.811024            |0.838653            |0.849943            |0.838491            |0.805004            |0.751553            |0.856253            |0.773308            |0.796879            |0.683452            
abs_error_cond                  |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|master              |observer            |journeyer           |apprentice          
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AlwaysMaster                    |0.202733 52981      |0.190231 48274      |0.169017 37937      |0.152940 30136      |0.140145 24623      |0.160110 32755      |0.156995 29773      |0.164359 13075      |0.177710 1642       |0.178459 41307      |0.172985 35506      |0.173505 15271      |0.186207 2030       |0.285827 254        |0.189479 45926      |0.180347 37979      |0.180960 16513      |0.190768 2318       |0.281366 322        |0.000000 17489      |0.600000 4698       |0.200000 21977      |0.400000 8817       
AlwaysJourneyer                 |0.134773 52981      |0.132005 48274      |0.134671 37937      |0.140370 30136      |0.145433 24623      |0.138147 32755      |0.143472 29773      |0.155778 13075      |0.204507 1642       |0.134994 41307      |0.140630 35506      |0.154738 15271      |0.201576 2030       |0.266929 254        |0.134738 45926      |0.140499 37979      |0.154545 16513      |0.201812 2318       |0.265217 322        |0.200000 17489      |0.400000 4698       |0.000000 21977      |0.200000 8817       
AlwaysApprentice                |0.232736 52981      |0.242615 48274      |0.262425 37937      |0.278186 30136      |0.290509 24623      |0.271116 32755      |0.276217 29773      |0.281254 13075      |0.302923 1642       |0.254049 41307      |0.262446 35506      |0.274795 15271      |0.296355 2030       |0.276378 254        |0.244646 45926      |0.257200 37979      |0.270272 16513      |0.293788 2318       |0.277640 322        |0.400000 17489      |0.200000 4698       |0.200000 21977      |0.000000 8817       
AlwaysObserver                  |0.397267 52981      |0.409769 48274      |0.430983 37937      |0.447060 30136      |0.459855 24623      |0.439890 32755      |0.443005 29773      |0.435641 13075      |0.422290 1642       |0.421541 41307      |0.427015 35506      |0.426495 15271      |0.413793 2030       |0.314173 254        |0.410521 45926      |0.419653 37979      |0.419040 16513      |0.409232 2318       |0.318634 322        |0.600000 17489      |0.000000 4698       |0.400000 21977      |0.200000 8817       
RandomTM                        |0.223114 52981      |0.225463 48274      |0.232662 37937      |0.239781 30136      |0.245610 24623      |0.236693 32755      |0.240287 29773      |0.248021 13075      |0.269011 1642       |0.229869 41307      |0.234623 35506      |0.245315 15271      |0.267154 2030       |0.284308 254        |0.227086 45926      |0.232994 37979      |0.243642 16513      |0.266833 2318       |0.289059 322        |0.301687 17489      |0.303674 4698       |0.166031 21977      |0.166619 8817       
EbayTM                          |0.101082 51821      |0.101018 48274      |0.101599 37937      |0.102984 30136      |0.103240 24623      |0.104577 32755      |0.109222 29773      |0.135227 13075      |0.189849 1642       |0.104640 41307      |0.111294 35506      |0.138239 15271      |0.192179 2030       |0.265682 254        |0.105931 45926      |0.113743 37979      |0.141325 16513      |0.196911 2318       |0.272450 322        |0.097703 17401      |0.349662 4442       |0.060934 21654      |0.079932 8324       
OutA_TM                         |0.113828 52038      |0.111805 47515      |0.112012 37355      |0.114091 29684      |0.116719 24254      |0.113284 32260      |0.115422 29307      |0.120628 12840      |0.153161 1604       |0.112472 40668      |0.114505 34941      |0.119807 14987      |0.149723 1987       |0.215427 251        |0.112712 45201      |0.114285 37370      |0.119055 16201      |0.148693 2265       |0.210083 316        |0.141218 17092      |0.161010 4633       |0.059326 21636      |0.170581 8677       
OutB_TM                         |0.145317 48834      |0.143399 45846      |0.142496 36522      |0.145550 28956      |0.149375 23550      |0.145038 31555      |0.150180 28599      |0.178710 11965      |0.233416 1392       |0.144718 39558      |0.150002 34000      |0.176127 13997      |0.224609 1745       |0.256571 229        |0.146059 43693      |0.151336 36205      |0.176141 15070      |0.223698 1978       |0.258394 291        |0.158141 16162      |0.376720 4056       |0.073784 20867      |0.190078 7749       
EdgesB_TM                       |0.113275 52275      |0.111711 48274      |0.111630 37937      |0.113530 30136      |0.114407 24623      |0.114453 32755      |0.118891 29773      |0.146089 13075      |0.197943 1642       |0.114218 41307      |0.119962 35506      |0.147093 15271      |0.197640 2030       |0.261961 254        |0.115378 45926      |0.121766 37979      |0.148769 16513      |0.200423 2318       |0.267509 322        |0.112511 17445      |0.363901 4499       |0.056882 21816      |0.126902 8515       
EdgesA_TM                       |0.123219 52607      |0.121889 47994      |0.123593 37723      |0.127345 29964      |0.131482 24475      |0.125887 32573      |0.129002 29594      |0.137046 12976      |0.176869 1626       |0.123518 41069      |0.127006 35287      |0.135941 15150      |0.172925 2011       |0.233459 254        |0.123344 45658      |0.126742 37742      |0.135236 16379      |0.171750 2294       |0.226131 321        |0.162913 17303      |0.218759 4658       |0.057593 21880      |0.157903 8766       
MoletrustTM_horizon2_threshold0 |0.101672 42147      |0.102273 40376      |0.104071 33007      |0.105689 26838      |0.106014 22237      |0.107406 28869      |0.112027 26256      |0.139111 11404      |0.195939 1404       |0.106729 35344      |0.113488 30583      |0.141206 13005      |0.198012 1679       |0.261568 206        |0.106977 38516      |0.114797 32280      |0.142692 13846      |0.199662 1866       |0.273351 242        |0.099849 14975      |0.344370 3633       |0.061809 17513      |0.075732 6026       
MoletrustTM_horizon3_threshold0 |0.102889 49331      |0.103128 46510      |0.104465 36842      |0.106006 29376      |0.106465 24043      |0.107753 31885      |0.112516 28977      |0.139349 12692      |0.194597 1583       |0.107304 40006      |0.114351 34415      |0.141992 14749      |0.197357 1948       |0.262811 244        |0.108097 44274      |0.116383 36698      |0.144442 15887      |0.201551 2206       |0.273805 299        |0.103799 16688      |0.332926 4299       |0.064213 20592      |0.076093 7752       
MoletrustTM_horizon4_threshold0 |0.103064 50576      |0.103191 47294      |0.104452 37213      |0.105948 29583      |0.106430 24172      |0.107741 32142      |0.112532 29199      |0.139441 12791      |0.194890 1594       |0.107354 40504      |0.114441 34804      |0.142204 14924      |0.197147 1976       |0.263304 249        |0.108224 44996      |0.116610 37211      |0.144781 16131      |0.201632 2254       |0.275907 314        |0.104814 16928      |0.331179 4376       |0.064874 21177      |0.075994 8095       
MoletrustTM_horizon2_threshold05|0.103849 42147      |0.103810 40376      |0.105046 33007      |0.106186 26838      |0.106129 22237      |0.108131 28869      |0.112559 26256      |0.139979 11404      |0.197354 1404       |0.107938 35344      |0.114378 30583      |0.142394 13005      |0.199066 1679       |0.271709 206        |0.108584 38516      |0.115963 32280      |0.144153 13846      |0.200982 1866       |0.284456 242        |0.100061 14975      |0.357826 3633       |0.062913 17513      |0.079116 6026       
MoletrustTM_horizon3_threshold05|0.105555 49331      |0.104997 46510      |0.105734 36842      |0.106825 29376      |0.107006 24043      |0.108737 31885      |0.113358 28977      |0.140548 12692      |0.196934 1583       |0.108775 40006      |0.115554 34415      |0.143549 14749      |0.199423 1948       |0.274869 244        |0.110012 44274      |0.117850 36698      |0.146192 15887      |0.203642 2206       |0.286407 299        |0.104539 16688      |0.348230 4299       |0.065386 20592      |0.079864 7752       
MoletrustTM_horizon4_threshold05|0.105855 50576      |0.105136 47294      |0.105755 37213      |0.106807 29583      |0.107005 24172      |0.108762 32142      |0.113416 29199      |0.140724 12791      |0.197327 1594       |0.108885 40504      |0.115720 34804      |0.143887 14924      |0.199266 1976       |0.275072 249        |0.110221 44996      |0.118158 37211      |0.146623 16131      |0.203691 2254       |0.287360 314        |0.105592 16928      |0.346449 4376       |0.066314 21177      |0.079787 8095       
AdvogatoGlobalTM                |0.096827 28903      |0.096861 28705      |0.097134 26833      |0.097104 23997      |0.097883 21117      |0.098492 24993      |0.102195 23005      |0.127023 10332      |0.164301 1423       |0.099289 27298      |0.103562 24565      |0.127617 11033      |0.166260 1559       |0.290833 240        |0.099334 27944      |0.104033 24894      |0.128398 11226      |0.167558 1646       |0.286692 263        |0.017467 14519      |0.518639 2028       |0.110394 10535      |0.181329 1821       
PageRankGlobalTM                |0.156153 52981      |0.149971 48274      |0.136356 37937      |0.127701 30136      |0.122127 24623      |0.130989 32755      |0.132599 29773      |0.148725 13075      |0.194611 1642       |0.142136 41307      |0.141560 35506      |0.159592 15271      |0.208965 2030       |0.281210 254        |0.148450 45926      |0.146602 37979      |0.165902 16513      |0.219483 2318       |0.282944 322        |0.172963 17489      |0.280490 4698       |0.136331 21977      |0.105965 8817       

coverage_cond
AlwaysMaster                    |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            
AlwaysJourneyer                 |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            
AlwaysApprentice                |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            
AlwaysObserver                  |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            
RandomTM                        |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            
EbayTM                          |0.978105            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |0.994968            |0.945509            |0.985303            |0.944085            
OutA_TM                         |0.982201            |0.984277            |0.984659            |0.985001            |0.985014            |0.984888            |0.984348            |0.982027            |0.976857            |0.984530            |0.984087            |0.981403            |0.978818            |0.988189            |0.984214            |0.983965            |0.981106            |0.977135            |0.981366            |0.977300            |0.986164            |0.984484            |0.984122            
OutB_TM                         |0.921727            |0.949704            |0.962701            |0.960844            |0.956423            |0.963364            |0.960568            |0.915105            |0.847747            |0.957659            |0.957585            |0.916574            |0.859606            |0.901575            |0.951378            |0.953290            |0.912614            |0.853322            |0.903727            |0.924124            |0.863346            |0.949493            |0.878870            
EdgesB_TM                       |0.986674            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |0.997484            |0.957642            |0.992674            |0.965748            
EdgesA_TM                       |0.992941            |0.994200            |0.994359            |0.994293            |0.993989            |0.994444            |0.993988            |0.992428            |0.990256            |0.994238            |0.993832            |0.992076            |0.990640            |1.000000            |0.994165            |0.993760            |0.991885            |0.989646            |0.996894            |0.989365            |0.991486            |0.995586            |0.994216            
MoletrustTM_horizon2_threshold0 |0.795512            |0.836392            |0.870048            |0.890563            |0.903099            |0.881362            |0.881873            |0.872199            |0.855055            |0.855642            |0.861347            |0.851614            |0.827094            |0.811024            |0.838653            |0.849943            |0.838491            |0.805004            |0.751553            |0.856253            |0.773308            |0.796879            |0.683452            
MoletrustTM_horizon3_threshold0 |0.931107            |0.963459            |0.971136            |0.974781            |0.976445            |0.973439            |0.973264            |0.970707            |0.964068            |0.968504            |0.969273            |0.965818            |0.959606            |0.960630            |0.964029            |0.966271            |0.962090            |0.951682            |0.928571            |0.954200            |0.915070            |0.936980            |0.879211            
MoletrustTM_horizon4_threshold0 |0.954606            |0.979699            |0.980916            |0.981650            |0.981684            |0.981285            |0.980721            |0.978279            |0.970767            |0.980560            |0.980229            |0.977277            |0.973399            |0.980315            |0.979750            |0.979778            |0.976867            |0.972390            |0.975155            |0.967923            |0.931460            |0.963598            |0.918113            
MoletrustTM_horizon2_threshold05|0.795512            |0.836392            |0.870048            |0.890563            |0.903099            |0.881362            |0.881873            |0.872199            |0.855055            |0.855642            |0.861347            |0.851614            |0.827094            |0.811024            |0.838653            |0.849943            |0.838491            |0.805004            |0.751553            |0.856253            |0.773308            |0.796879            |0.683452            
MoletrustTM_horizon3_threshold05|0.931107            |0.963459            |0.971136            |0.974781            |0.976445            |0.973439            |0.973264            |0.970707            |0.964068            |0.968504            |0.969273            |0.965818            |0.959606            |0.960630            |0.964029            |0.966271            |0.962090            |0.951682            |0.928571            |0.954200            |0.915070            |0.936980            |0.879211            
MoletrustTM_horizon4_threshold05|0.954606            |0.979699            |0.980916            |0.981650            |0.981684            |0.981285            |0.980721            |0.978279            |0.970767            |0.980560            |0.980229            |0.977277            |0.973399            |0.980315            |0.979750            |0.979778            |0.976867            |0.972390            |0.975155            |0.967923            |0.931460            |0.963598            |0.918113            
AdvogatoGlobalTM                |0.545535            |0.594627            |0.707304            |0.796290            |0.857613            |0.763029            |0.772680            |0.790210            |0.866626            |0.660857            |0.691855            |0.722481            |0.767980            |0.944882            |0.608457            |0.655467            |0.679828            |0.710095            |0.816770            |0.830179            |0.431673            |0.479365            |0.206533            
PageRankGlobalTM                |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            

Descriptions of the trust metrics as we named them in the code:

AlwaysMaster: always return 1.0

AlwaysApprentice: always return 0.8

AlwaysJourneyer: always return 0.6

AlwaysObserver: always return 0.4

RandomTM: always return random number in [0.4,1]

EbayTM(a,b): return average of the values of trust on the edges going to the target b.

OutA_TM(a,b): Average outgoing links of a

OutB_TM(a,b): Average outgoing links of b

EdgesB_TM(a,b): Average of outgoing and incoming edges of b

EdgesA_TM(a,b): Average of outgoing and incoming edges of a

MoletrustTM_horizon2_threshold0: moletrust with horizon 2 and threshold 0

MoletrustTM_horizon3_threshold0,

MoletrustTM_horizon4_threshold0,

MoletrustTM_horizon2_threshold05,

MoletrustTM_horizon3_threshold05,

MoletrustTM_horizon4_threshold05,

AdvogatoGlobalTM: advogato used from a global point of view (raph, federico, ... as seeds)

AdvogatoTM: advogato but used from a local point of view (current user)

PageRankGlobalTM: pagerank once, rescaled

PageRankTM0: pagerank for every edge removed, rescaled

nicetable from power

coverage_cond                   |every_edge         |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|master             |observer            |journeyer           |apprentice  
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon4_threshold05|0.954606            |0.979699            |0.980916            |0.981650            |0.981684            |0.981285            |0.980721            |0.978279            |0.970767            |0.980560            |0.980229            |0.977277            |0.973399            |0.980315            |0.979750            |0.979778            |0.976867            |0.972390            |0.975155            |0.967923            |0.931460            |0.963598            |0.918113    

OutB_TM                         |0.921727            |0.949704            |0.962701            |0.960844            |0.956423            |0.963364            |0.960568            |0.915105            |0.847747            |0.957659            |0.957585            |0.916574            |0.859606            |0.901575            |0.951378            |0.953290            |0.912614            |0.853322            |0.903727            |0.924124            |0.863346            |0.949493            |0.878870    

AlwaysMaster                    |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000    

AlwaysApprentice                |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000    

AlwaysJourneyer                 |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000    

MoletrustTM_horizon4_threshold0 |0.954606            |0.979699            |0.980916            |0.981650            |0.981684            |0.981285            |0.980721            |0.978279            |0.970767            |0.980560            |0.980229            |0.977277            |0.973399            |0.980315            |0.979750            |0.979778            |0.976867            |0.972390            |0.975155            |0.967923            |0.931460            |0.963598            |0.918113    

MoletrustTM_horizon3_threshold05|0.931107            |0.963459            |0.971136            |0.974781            |0.976445            |0.973439            |0.973264            |0.970707            |0.964068            |0.968504            |0.969273            |0.965818            |0.959606            |0.960630            |0.964029            |0.966271            |0.962090            |0.951682            |0.928571            |0.954200            |0.915070            |0.936980            |0.879211    

MoletrustTM_horizon2_threshold0 |0.795512            |0.836392            |0.870048            |0.890563            |0.903099            |0.881362            |0.881873            |0.872199            |0.855055            |0.855642            |0.861347            |0.851614            |0.827094            |0.811024            |0.838653            |0.849943            |0.838491            |0.805004            |0.751553            |0.856253            |0.773308            |0.796879            |0.683452    

MoletrustTM_horizon3_threshold0 |0.931107            |0.963459            |0.971136            |0.974781            |0.976445            |0.973439            |0.973264            |0.970707            |0.964068            |0.968504            |0.969273            |0.965818            |0.959606            |0.960630            |0.964029            |0.966271            |0.962090            |0.951682            |0.928571            |0.954200            |0.915070            |0.936980            |0.879211    

MoletrustTM_horizon2_threshold05|0.795512            |0.836392            |0.870048            |0.890563            |0.903099            |0.881362            |0.881873            |0.872199            |0.855055            |0.855642            |0.861347            |0.851614            |0.827094            |0.811024            |0.838653            |0.849943            |0.838491            |0.805004            |0.751553            |0.856253            |0.773308            |0.796879            |0.683452    

EbayTM                          |0.978105            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |0.994968            |0.945509            |0.985303            |0.944085    

OutA_TM                         |0.982201            |0.984277            |0.984659            |0.985001            |0.985014            |0.984888            |0.984348            |0.982027            |0.976857            |0.984530            |0.984087            |0.981403            |0.978818            |0.988189            |0.984214            |0.983965            |0.981106            |0.977135            |0.981366            |0.977300            |0.986164            |0.984484            |0.984122    

PageRankGlobalTM                |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000    

EdgesA_TM                       |0.992941            |0.994200            |0.994359            |0.994293            |0.993989            |0.994444            |0.993988            |0.992428            |0.990256            |0.994238            |0.993832            |0.992076            |0.990640            |1.000000            |0.994165            |0.993760            |0.991885            |0.989646            |0.996894            |0.989365            |0.991486            |0.995586            |0.994216    

AlwaysObserver                  |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000    

RandomTM                        |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000    

AdvogatoGlobalTM                |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000    

EdgesB_TM                       |0.986674            |1.000000            |1.000000            |1.000000           |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000           |1.000000            |1.000000            |1.000000            |1.000000            |1.000000            |1.000000           |1.000000            |1.000000            |1.000000            |0.997484            |0.957642            |0.992674           |0.965748  


abs_error_cond                  |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|master            |observer            |journeyer           |apprentice  

--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon4_threshold05|0.105855 50576      |0.105136 47294      |0.105755 37213      |0.106807 29583      |0.107005 24172      |0.108762 32142      |0.113416 29199      |0.140724 12791      |0.197327 1594       |0.108885 40504      |0.115720 34804      |0.143887 14924      |0.199266 1976       |0.275072 249        |0.110221 44996      |0.118158 37211      |0.146623 16131      |0.203691 2254       |0.287360 314        |0.105592 16928      |0.346449 4376       |0.066314 21177      |0.079787 8095
OutB_TM                         |0.145317 48834      |0.143399 45846      |0.142496 36522      |0.145550 28956      |0.149375 23550      |0.145038 31555      |0.150180 28599      |0.178710 11965      |0.233416 1392       |0.144718 39558      |0.150002 34000      |0.176127 13997      |0.224609 1745       |0.256571 229        |0.146059 43693      |0.151336 36205      |0.176141 15070      |0.223698 1978       |0.258394 291        |0.158141 16162      |0.376720 4056       |0.073784 20867      |0.190078 7749
AlwaysMaster                    |0.202733 52981      |0.190231 48274      |0.169017 37937      |0.152940 30136      |0.140145 24623      |0.160110 32755      |0.156995 29773      |0.164359 13075      |0.177710 1642       |0.178459 41307      |0.172985 35506      |0.173505 15271      |0.186207 2030       |0.285827 254        |0.189479 45926      |0.180347 37979      |0.180960 16513      |0.190768 2318       |0.281366 322        |0.000000 17489      |0.6000004698       |0.200000 21977      |0.400000 8817
AlwaysApprentice                |0.232736 52981      |0.242615 48274      |0.262425 37937      |0.278186 30136      |0.290509 24623      |0.271116 32755      |0.276217 29773      |0.281254 13075      |0.302923 1642       |0.254049 41307      |0.262446 35506      |0.274795 15271      |0.296355 2030       |0.276378 254        |0.244646 45926      |0.257200 37979      |0.270272 16513      |0.293788 2318       |0.277640 322        |0.400000 17489      |0.200000 4698       |0.200000 21977      |0.000000 8817
AlwaysJourneyer                 |0.134773 52981      |0.132005 48274      |0.134671 37937      |0.140370 30136      |0.145433 24623      |0.138147 32755      |0.143472 29773      |0.155778 13075      |0.204507 1642       |0.134994 41307      |0.140630 35506      |0.154738 15271      |0.201576 2030       |0.266929 254        |0.134738 45926      |0.140499 37979      |0.154545 16513      |0.201812 2318       |0.265217 322        |0.200000 17489      |0.400000 4698       |0.000000 21977      |0.200000 8817
MoletrustTM_horizon4_threshold0 |0.103064 50576      |0.103191 47294      |0.104452 37213      |0.105948 29583      |0.106430 24172      |0.107741 32142      |0.112532 29199      |0.139441 12791      |0.194890 1594       |0.107354 40504      |0.114441 34804      |0.142204 14924      |0.197147 1976       |0.263304 249        |0.108224 44996      |0.116610 37211      |0.144781 16131      |0.201632 2254       |0.275907 314        |0.104814 16928      |0.331179 4376       |0.064874 21177      |0.075994 8095
MoletrustTM_horizon3_threshold05|0.105555 49331      |0.104997 46510      |0.105734 36842      |0.106825 29376      |0.107006 24043      |0.108737 31885      |0.113358 28977      |0.140548 12692      |0.196934 1583       |0.108775 40006      |0.115554 34415      |0.143549 14749      |0.199423 1948       |0.274869 244        |0.110012 44274      |0.117850 36698      |0.146192 15887      |0.203642 2206       |0.286407 299        |0.104539 16688      |0.348230 4299       |0.065386 20592      |0.079864 7752
MoletrustTM_horizon2_threshold0 |0.101672 42147      |0.102273 40376      |0.104071 33007      |0.105689 26838      |0.106014 22237      |0.107406 28869      |0.112027 26256      |0.139111 11404      |0.195939 1404       |0.106729 35344      |0.113488 30583      |0.141206 13005      |0.198012 1679       |0.261568 206        |0.106977 38516      |0.114797 32280      |0.142692 13846      |0.199662 1866       |0.273351 242        |0.099849 14975      |0.344370 3633       |0.061809 17513      |0.075732 6026
MoletrustTM_horizon3_threshold0 |0.102889 49331      |0.103128 46510      |0.104465 36842      |0.106006 29376      |0.106465 24043      |0.107753 31885      |0.112516 28977      |0.139349 12692      |0.194597 1583       |0.107304 40006      |0.114351 34415      |0.141992 14749      |0.197357 1948       |0.262811 244        |0.108097 44274      |0.116383 36698      |0.144442 15887      |0.201551 2206       |0.273805 299        |0.103799 16688      |0.332926 4299       |0.064213 20592      |0.076093 7752
MoletrustTM_horizon2_threshold05|0.103849 42147      |0.103810 40376      |0.105046 33007      |0.106186 26838      |0.106129 22237      |0.108131 28869      |0.112559 26256      |0.139979 11404      |0.197354 1404       |0.107938 35344      |0.114378 30583      |0.142394 13005      |0.199066 1679       |0.271709 206        |0.108584 38516      |0.115963 32280      |0.144153 13846      |0.200982 1866       |0.284456 242        |0.100061 14975      |0.357826 3633       |0.062913 17513      |0.079116 6026
EbayTM                          |0.101082 51821      |0.101018 48274      |0.101599 37937      |0.102984 30136      |0.103240 24623      |0.104577 32755      |0.109222 29773      |0.135227 13075      |0.189849 1642       |0.104640 41307      |0.111294 35506      |0.138239 15271      |0.192179 2030       |0.265682 254        |0.105931 45926      |0.113743 37979      |0.141325 16513      |0.196911 2318       |0.272450 322        |0.097703 17401      |0.349662 4442       |0.060934 21654      |0.079932 8324
OutA_TM                         |0.113828 52038      |0.111805 47515      |0.112012 37355      |0.114091 29684      |0.116719 24254      |0.113284 32260      |0.115422 29307      |0.120628 12840      |0.153161 1604       |0.112472 40668      |0.114505 34941      |0.119807 14987      |0.149723 1987       |0.215427 251        |0.112712 45201      |0.114285 37370      |0.119055 16201      |0.148693 2265       |0.210083 316        |0.141218 17092      |0.161010 4633       |0.059326 21636      |0.170581 8677
PageRankGlobalTM                |0.156153 52981      |0.149971 48274      |0.136356 37937      |0.127701 30136      |0.122127 24623      |0.130989 32755      |0.132599 29773      |0.148725 13075      |0.194611 1642       |0.142136 41307      |0.141560 35506      |0.159592 15271      |0.208965 2030       |0.281210 254        |0.148450 45926      |0.146602 37979      |0.165902 16513      |0.219483 2318       |0.282944 322        |0.172963 17489      |0.280490 4698       |0.136331 21977      |0.105965 8817
EdgesA_TM                       |0.123219 52607      |0.121889 47994      |0.123593 37723      |0.127345 29964      |0.131482 24475      |0.125887 32573      |0.129002 29594      |0.137046 12976      |0.176869 1626       |0.123518 41069      |0.127006 35287      |0.135941 15150      |0.172925 2011       |0.233459 254        |0.123344 45658      |0.126742 37742      |0.135236 16379      |0.171750 2294       |0.226131 321        |0.162913 17303      |0.218759 4658       |0.057593 21880      |0.157903 8766
AlwaysObserver                  |0.397267 52981      |0.409769 48274      |0.430983 37937      |0.447060 30136      |0.459855 24623      |0.439890 32755      |0.443005 29773      |0.435641 13075      |0.422290 1642       |0.421541 41307      |0.427015 35506      |0.426495 15271      |0.413793 2030       |0.314173 254        |0.410521 45926      |0.419653 37979      |0.419040 16513      |0.409232 2318       |0.318634 322        |0.600000 17489      |0.000000 4698       |0.400000 21977      |0.200000 8817
RandomTM                        |0.223114 52981      |0.225463 48274      |0.232662 37937      |0.239781 30136      |0.245610 24623      |0.236693 32755      |0.240287 29773      |0.248021 13075      |0.269011 1642       |0.229869 41307      |0.234623 35506      |0.245315 15271      |0.267154 2030       |0.284308 254        |0.227086 45926      |0.232994 37979      |0.243642 16513      |0.266833 2318       |0.289059 322        |0.301687 17489      |0.303674 4698       |0.166031 21977      |0.166619 8817
AdvogatoGlobalTM                |0.202733 52981      |0.190231 48274      |0.169017 37937      |0.152940 30136      |0.140145 24623      |0.160110 32755      |0.156995 29773      |0.164359 13075      |0.177710 1642       |0.178459 41307      |0.172985 35506      |0.173505 15271      |0.186207 2030       |0.285827 254        |0.189479 45926      |0.180347 37979      |0.180960 16513      |0.190768 2318       |0.281366 322        |0.000000 17489      |0.600000 4698       |0.200000 21977      |0.400000 8817
EdgesB_TM                       |0.113275 52275      |0.111711 48274      |0.111630 37937      |0.113530 30136      |0.114407 24623      |0.114453 32755      |0.118891 29773      |0.146089 13075      |0.197943 1642       |0.114218 41307      |0.119962 35506      |0.147093 15271      |0.197640 2030       |0.261961 254        |0.115378 45926      |0.121766 37979      |0.148769 16513      |0.200423 2318       |0.267509 322        |0.112511 17445      |0.363901 4499       |0.056882 21816      |0.126902 8515

yes_no_error_cond               |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|master              |observer            |journeyer           |apprentice          
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AlwaysMaster                    |0.330099 52981      |0.354435 48274      |0.414134 37937      |0.468576 30136      |0.513219 24623      |0.445092 32755      |0.466194 29773      |0.478547 13075      |0.566991 1642       |0.391338 41307      |0.419112 35506      |0.453081 15271      |0.538424 2030       |0.452756 254        |0.363149 45926      |0.400379 37979      |0.433961 16513      |0.527610 2318       |0.459627 322        |1.000000 17489      |0.000000 4698       |0.000000 21977      |0.000000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AlwaysJourneyer                 |0.414809 52981      |0.422091 48274      |0.405251 37937      |0.375962 30136      |0.349470 24623      |0.387330 32755      |0.365667 29773      |0.335143 13075      |0.179050 1642       |0.406299 41307      |0.385428 35506      |0.347063 15271      |0.198522 2030       |0.070866 254        |0.411619 45926      |0.391374 37979      |0.355356 16513      |0.202330 2318       |0.071429 322        |0.000000 17489      |0.000000 4698       |1.000000 21977      |0.000000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AlwaysApprentice                |0.166418 52981      |0.141360 48274      |0.102011 37937      |0.077648 30136      |0.060675 24623      |0.089513 32755      |0.085111 29773      |0.072275 13075      |0.052375 1642       |0.121093 41307      |0.106883 35506      |0.079104 15271      |0.056650 2030       |0.070866 254        |0.139921 45926      |0.114379 37979      |0.082602 16513      |0.058671 2318       |0.071429 322        |0.000000 17489      |0.000000 4698       |0.000000 21977      |1.000000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AlwaysObserver                  |0.088673 52981      |0.082115 48274      |0.078604 37937      |0.077814 30136      |0.076636 24623      |0.078064 32755      |0.083028 29773      |0.114034 13075      |0.201583 1642       |0.081270 41307      |0.088577 35506      |0.120752 15271      |0.206404 2030       |0.405512 254        |0.085311 45926      |0.093868 37979      |0.128081 16513      |0.211389 2318       |0.397516 322        |0.000000 17489      |1.000000 4698       |0.000000 21977      |0.000000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
RandomTM                        |0.000000 52981      |0.000000 48274      |0.000000 37937      |0.000000 30136      |0.000000 24623      |0.000000 32755      |0.000000 29773      |0.000000 13075      |0.000000 1642       |0.000000 41307      |0.000000 35506      |0.000000 15271      |0.000000 2030       |0.000000 254        |0.000000 45926      |0.000000 37979      |0.000000 16513      |0.000000 2318       |0.000000 322        |0.000000 17489      |0.000000 4698       |0.000000 21977      |0.000000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
EbayTM                          |0.082727 51821      |0.055869 48274      |0.028943 37937      |0.019279 30136      |0.015717 24623      |0.010869 32755      |0.007960 29773      |0.011472 13075      |0.019488 1642       |0.017576 41307      |0.012927 35506      |0.012442 15271      |0.015764 2030       |0.003937 254        |0.021143 45926      |0.017246 37979      |0.016290 16513      |0.019845 2318       |0.003106 322        |0.018390 17401      |0.013507 4442       |0.111619 21654      |0.179000 8324       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
OutA_TM                         |0.071486 52038      |0.071725 47515      |0.072253 37355      |0.072868 29684      |0.073596 24254      |0.072753 32260      |0.074351 29307      |0.081075 12840      |0.072319 1604       |0.072366 40668      |0.073667 34941      |0.079869 14987      |0.068948 1987       |0.055777 251        |0.072255 45201      |0.074364 37370      |0.080674 16201      |0.068433 2265       |0.060127 316        |0.085186 17092      |0.133391 4633       |0.069837 21636      |0.015558 8677       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
OutB_TM                         |0.089139 48834      |0.081599 45846      |0.070177 36522      |0.069174 28956      |0.072527 23550      |0.068832 31555      |0.069443 28599      |0.042039 11965      |0.035920 1392       |0.073487 39558      |0.073706 34000      |0.050154 13997      |0.068195 1745       |0.104803 229        |0.079441 43693      |0.077420 36205      |0.059257 15070      |0.080890 1978       |0.137457 291        |0.114775 16162      |0.039941 4056       |0.097235 20867      |0.039618 7749       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
EdgesB_TM                       |0.039350 52275      |0.023159 48274      |0.011414 37937      |0.006471 30136      |0.006823 24623      |0.007388 32755      |0.003325 29773      |0.004283 13075      |0.000000 1642       |0.011596 41307      |0.007999 35506      |0.006548 15271      |0.004926 2030       |0.000000 254        |0.015285 45926      |0.010006 37979      |0.008720 16513      |0.008197 2318       |0.000000 322        |0.012267 17445      |0.009558 4499       |0.058535 21816      |0.061421 8515       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
EdgesA_TM                       |0.034786 52607      |0.034275 47994      |0.035469 37723      |0.036043 29964      |0.035955 24475      |0.035612 32573      |0.035582 29594      |0.035681 12976      |0.026445 1626       |0.035185 41069      |0.034744 35287      |0.034917 15150      |0.024863 2011       |0.027559 254        |0.034189 45658      |0.034312 37742      |0.034495 16379      |0.023976 2294       |0.021807 321        |0.044790 17303      |0.007299 4658       |0.040722 21880      |0.014830 8766       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon2_threshold0 |0.169122 42147      |0.152665 40376      |0.117248 33007      |0.100902 26838      |0.092324 22237      |0.089750 28869      |0.080401 26256      |0.048843 11404      |0.028490 1404       |0.105478 35344      |0.088219 30583      |0.056209 13005      |0.036927 1679       |0.058252 206        |0.117665 38516      |0.095570 32280      |0.064640 13846      |0.051447 1866       |0.070248 242        |0.133222 14975      |0.024773 3633       |0.209673 17513      |0.227514 6026       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon3_threshold0 |0.165859 49331      |0.145990 46510      |0.110960 36842      |0.096065 29376      |0.088550 24043      |0.084679 31885      |0.075646 28977      |0.045225 12692      |0.027164 1583       |0.098410 40006      |0.082348 34415      |0.051936 14749      |0.034908 1948       |0.057377 244        |0.109003 44274      |0.088642 36698      |0.059608 15887      |0.047144 2206       |0.066890 299        |0.128176 16688      |0.028379 4299       |0.202457 20592      |0.226006 7752       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon4_threshold0 |0.167510 50576      |0.145431 47294      |0.110418 37213      |0.095663 29583      |0.088408 24172      |0.084127 32142      |0.075140 29199      |0.044875 12791      |0.026976 1594       |0.097497 40504      |0.081600 34804      |0.051461 14924      |0.035425 1976       |0.056225 249        |0.107898 44996      |0.087716 37211      |0.059017 16131      |0.047028 2254       |0.063694 314        |0.127245 16928      |0.031079 4376       |0.203523 21177      |0.231254 8095       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AdvogatoGlobalTM                |0.649448 28903      |0.649399 28705      |0.650095 26833      |0.654749 23997      |0.654402 21117      |0.648021 24993      |0.639948 23005      |0.587302 10332      |0.594519 1423       |0.640999 27298      |0.633259 24565      |0.583522 11033      |0.578576 1559       |0.379167 240        |0.640638 27944      |0.632321 24894      |0.581774 11226      |0.574727 1646       |0.391635 263        |0.921620 14519      |0.000000 2028       |0.448030 10535      |0.367930 1821       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
PageRankGlobalTM                |0.013854 52981      |0.015205 48274      |0.019348 37937      |0.024356 30136      |0.029810 24623      |0.022409 32755      |0.024653 29773      |0.000000 13075      |0.000000 1642       |0.017769 41307      |0.020673 35506      |0.000000 15271      |0.000000 2030       |0.000000 254        |0.015982 45926      |0.019326 37979      |0.000000 16513      |0.000000 2318       |0.000000 322        |0.041969 17489      |0.000000 4698       |0.000000 21977      |0.000000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------


--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
root_mean_squared_error_cond    |every_edge          |edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_connected_no|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|edge_to_controversia|master              |observer            |journeyer           |apprentice  --------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AlwaysMaster                    |0.274120 52981      |0.262797 48274      |0.246636 37937      |0.235532 30136      |0.226441 24623      |0.240663 32755      |0.241111 29773      |0.256948 13075      |0.296837 1642       |0.254723 41307      |0.253783 35506      |0.264594 15271      |0.302176 2030       |0.400197 254        |0.263750 45926      |0.260284 37979      |0.271182 16513      |0.305910 2318       |0.396726 322        |0.000000 17489      |0.600000 4698       |0.200000 21977      |0.400000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AlwaysJourneyer                 |0.184522 52981      |0.181577 48274      |0.182270 37937      |0.185200 30136      |0.187663 24623      |0.184050 32755      |0.187981 29773      |0.200695 13075      |0.238805 1642       |0.183031 41307      |0.187649 35506      |0.201513 15271      |0.238385 2030       |0.292962 254        |0.183773 45926      |0.188704 37979      |0.202868 16513      |0.239319 2318       |0.291281 322        |0.200000 17489      |0.400000 4698       |0.000000 21977      |0.200000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AlwaysApprentice                |0.270102 52981      |0.277269 48274      |0.292601 37937      |0.305161 30136      |0.314896 24623      |0.299717 32755      |0.304202 29773      |0.307465 13075      |0.325490 1642       |0.286560 41307      |0.293288 35506      |0.302003 15271      |0.319914 2030       |0.302483 254        |0.279251 45926      |0.288912 37979      |0.297945 16513      |0.317752 2318       |0.303806 322        |0.400000 17489      |0.200000 4698       |0.200000 21977      |0.000000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AlwaysObserver                  |0.438021 52981      |0.448091 48274      |0.466914 37937      |0.481609 30136      |0.493053 24623      |0.475170 32755      |0.479313 29773      |0.478321 13075      |0.484623 1642       |0.459057 41307      |0.465644 35506      |0.470960 15271      |0.477349 2030       |0.420910 254        |0.449655 45926      |0.459708 37979      |0.465174 16513      |0.473982 2318       |0.423971 322        |0.600000 17489      |0.000000 4698       |0.400000 21977      |0.200000 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
RandomTM                        |0.271913 52981      |0.274493 48274      |0.282354 37937      |0.289877 30136      |0.295797 24623      |0.286631 32755      |0.290464 29773      |0.298541 13075      |0.318270 1642       |0.279416 41307      |0.284635 35506      |0.295839 15271      |0.316107 2030       |0.329072 254        |0.276295 45926      |0.282862 37979      |0.294001 16513      |0.315780 2318       |0.332285 322        |0.347849 17489      |0.349250 4698       |0.199476 21977      |0.200248 8817       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
EbayTM                          |0.148024 51821      |0.147229 48274      |0.148955 37937      |0.151697 30136      |0.153516 24623      |0.152117 32755      |0.156884 29773      |0.181722 13075      |0.229925 1642       |0.150368 41307      |0.157893 35506      |0.183921 15271      |0.232092 2030       |0.281754 254        |0.150853 45926      |0.160255 37979      |0.186970 16513      |0.237573 2318       |0.290250 322        |0.121451 17401      |0.375466 4442       |0.083128 21654      |0.111203 8324       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
OutA_TM                         |0.148075 52038      |0.145593 47515      |0.145769 37355      |0.147557 29684      |0.149865 24254      |0.146543 32260      |0.148740 29307      |0.156723 12840      |0.193986 1604       |0.146035 40668      |0.148332 34941      |0.156154 14987      |0.189740 1987       |0.262877 251        |0.146341 45201      |0.148308 37370      |0.155642 16201      |0.188808 2265       |0.257722 316        |0.166721 17092      |0.219363 4633       |0.080682 21636      |0.186602 8677       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
OutB_TM                         |0.196673 48834      |0.194213 45846      |0.193657 36522      |0.198160 28956      |0.202094 23550      |0.196941 31555      |0.202643 28599      |0.232111 11965      |0.288593 1392       |0.195516 39558      |0.202169 34000      |0.229730 13997      |0.283314 1745       |0.308999 229        |0.197011 43693      |0.203971 36205      |0.230645 15070      |0.284388 1978       |0.320444 291        |0.201380 16162      |0.401606 4056       |0.105581 20867      |0.211519 7749       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
EdgesB_TM                       |0.158617 52275      |0.156263 48274      |0.156750 37937      |0.159438 30136      |0.160758 24623      |0.159743 32755      |0.164470 29773      |0.191052 13075      |0.237295 1642       |0.158599 41307      |0.165460 35506      |0.192160 15271      |0.237901 2030       |0.282335 254        |0.159590 45926      |0.167618 37979      |0.194361 16513      |0.242092 2318       |0.291565 322        |0.135555 17445      |0.384773 4499       |0.079024 21816      |0.150289 8515       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
EdgesA_TM                       |0.156493 52607      |0.154974 47994      |0.156805 37723      |0.160203 29964      |0.163972 24475      |0.158665 32573      |0.161613 29594      |0.171284 12976      |0.212386 1626       |0.156468 41069      |0.160058 35287      |0.170553 15150      |0.208575 2011       |0.270517 254        |0.156259 45658      |0.159921 37742      |0.170028 16379      |0.207367 2294       |0.263132 321        |0.185733 17303      |0.252633 4658       |0.076638 21880      |0.174079 8766       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon2_threshold0 |0.151917 42147      |0.152073 40376      |0.153720 33007      |0.156053 26838      |0.157220 22237      |0.156772 28869      |0.161531 26256      |0.186893 11404      |0.235436 1404       |0.155377 35344      |0.162678 30583      |0.189224 13005      |0.238574 1679       |0.294741 206        |0.155598 38516      |0.164402 32280      |0.191456 13846      |0.243050 1866       |0.312643 242        |0.130784 14975      |0.371921 3633       |0.090191 17513      |0.108980 6026       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon3_threshold0 |0.152132 49331      |0.151747 46510      |0.152913 36842      |0.155285 29376      |0.156687 24043      |0.155978 31885      |0.160814 28977      |0.185965 12692      |0.233256 1583       |0.154686 40006      |0.162278 34415      |0.188713 14749      |0.237245 1948       |0.295193 244        |0.155429 44274      |0.164796 36698      |0.192010 15887      |0.244419 2206       |0.311558 299        |0.135460 16688      |0.362108 4299       |0.093221 20592      |0.109451 7752       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
MoletrustTM_horizon4_threshold0 |0.152350 50576      |0.151711 47294      |0.152813 37213      |0.155150 29583      |0.156596 24172      |0.155882 32142      |0.160743 29199      |0.185974 12791      |0.233385 1594       |0.154606 40504      |0.162251 34804      |0.188794 14924      |0.236859 1976       |0.295182 249        |0.155436 44996      |0.164933 37211      |0.192260 16131      |0.244514 2254       |0.313953 314        |0.137017 16928      |0.360860 4376       |0.094476 21177      |0.109599 8095       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
AdvogatoGlobalTM                |0.183893 28903      |0.183970 28705      |0.184996 26833      |0.186769 23997      |0.188574 21117      |0.187353 24993      |0.192405 23005      |0.223598 10332      |0.283389 1423       |0.186448 27298      |0.192681 24565      |0.223191 11033      |0.282025 1559       |0.392216 240        |0.186362 27944      |0.193246 24894      |0.224009 11226      |0.282972 1646       |0.390184 263        |0.064882 14519      |0.533697 2028       |0.148589 10535      |0.241313 1821       
--------------------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------+--------------------
PageRankGlobalTM                |0.198903 52981      |0.191766 48274      |0.178803 37937      |0.172936 30136      |0.170978 24623      |0.174959 32755      |0.177485 29773      |0.195917 13075      |0.246866 1642       |0.184647 41307      |0.185028 35506      |0.205565 15271      |0.257938 2030       |0.327913 254        |0.190920 45926      |0.190214 37979      |0.211732 16513      |0.267770 2318       |0.328290 322        |0.215591 17489      |0.328128 4698       |0.169640 21977      |0.128201 8817       
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