TY  - CONF
ID  - www200975
UR  - http://www2009.eprints.org/75/
A1  - Kunegis, Jérôme
A1  - Lommatzsch, Andreas
A1  - Bauckhage, Christian
Y1  - 2009/04//
N2  - We analyse the corpus of user relationships of the Slash-
dot 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 en-
dorsements. We adapt social network analysis techniques to
the problem of negative edge weights. In particular, we con-
sider signed variants of global network characteristics such as
the clustering coefficient, node-level characteristics such as
centrality and popularity measures, and link-level character-
istics 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.

TI  - The Slashdot Zoo: Mining a Social Network with Negative Edges
SP  - 741
M2  - Madrid, Spain
AV  - public
EP  - 741
T2  - 18th International World Wide Web Conference
ER  -