Name
Abstract | ||
|---|---|---|
We analyse the corpus of user relationships of the Slashdot technology news site. The data was collected from the Slashdot Zoo feature where users of the website can tag other users as friends and foes, providing positive and negative endorsements. We adapt social network analysis techniques to the problem of negative edge weights. In particular, we consider signed variants of global network characteristics such as the clustering coefficient, node-level characteristics such as centrality and popularity measures, and link-level characteristics such as distances and similarity measures. We evaluate these measures on the task of identifying unpopular users, as well as on the task of predicting the sign of links and show that the network exhibits multiplicative transitivity which allows algebraic methods based on matrix multiplication to be used. We compare our methods to traditional methods which are only suitable for positively weighted edges. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1526709.1526809 | Proceedings of the 18th international conference on World wide web |
Keywords | Field | DocType |
slashdot zoo,algebraic method,negative edge weight,slashdot zoo feature,negative endorsement,global network characteristic,link-level characteristic,social network analysis technique,matrix multiplication,clustering coefficient,slashdot technology news site,social network,social network analysis | Data mining,Social network,Global network,Computer science,Popularity,Artificial intelligence,Clustering coefficient,Transitive relation,World Wide Web,Social network analysis,Centrality,Matrix multiplication,Machine learning | Conference |
Volume | ISSN | Citations |
abs/1710.11395 | Proc. WWW 2009 | 136 |
PageRank | References | Authors |
6.37 | 21 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jérôme Kunegis | 1 | 874 | 51.20 |
| Andreas Lommatzsch | 2 | 479 | 40.83 |
| Christian Bauckhage | 3 | 1979 | 195.86 |