Browse wiki

Jump to: navigation, search
Predicting positive and negative links in online social networks
Abstract We study online social networks in which rWe study online social networks in which relationships can be either positive (indicating relations such as friendship) or negative (indicating relations such as opposition or antagonism). Such a mix of positive and negative links arise in a variety of online settings; we study datasets from Epinions, Slashdot and Wikipedia. We find that the signs of links in the underlying social networks can be predicted with high accuracy, using models that generalize across this diverse range of sites. These models provide insight into some of the fundamental principles that drive the formation of signed links in networks, shedding light on theories of balance and status from social psychology; they also suggest social computing applications by which the attitude of one user toward another can be estimated from evidence provided by their relationships with other members of the surrounding social network.members of the surrounding social network.
Abstractsub We study online social networks in which rWe study online social networks in which relationships can be either positive (indicating relations such as friendship) or negative (indicating relations such as opposition or antagonism). Such a mix of positive and negative links arise in a variety of online settings; we study datasets from Epinions, Slashdot and Wikipedia. We find that the signs of links in the underlying social networks can be predicted with high accuracy, using models that generalize across this diverse range of sites. These models provide insight into some of the fundamental principles that drive the formation of signed links in networks, shedding light on theories of balance and status from social psychology; they also suggest social computing applications by which the attitude of one user toward another can be estimated from evidence provided by their relationships with other members of the surrounding social network.members of the surrounding social network.
Bibtextype inproceedings  +
Doi 10.1145/1772690.1772756  +
Has author Leskovec J. + , Huttenlocher D. + , Kleinberg J. +
Has extra keyword Dataset + , Diverse range + , Fundamental principles + , In-network + , On-line setting + , Shedding light + , Social computing + , Social Networks + , Social psychology + , Structural balance + , Wikipedia + , World Wide Web + , Social networking (online) +
Has keyword Distrust + , Negative edges + , Positive edges + , Signed networks + , Status theory + , Structural balance + , Trust +
Isbn 9781605587998  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 641–650  +
Published in Proceedings of the 19th International Conference on World Wide Web, WWW '10 +
Title Predicting positive and negative links in online social networks +
Type conference paper  +
Year 2010 +
Creation dateThis property is a special property in this wiki. 8 November 2014 05:48:39  +
Categories Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 8 November 2014 05:48:39  +
DateThis property is a special property in this wiki. 2010  +
hide properties that link here 
Predicting positive and negative links in online social networks + Title
 

 

Enter the name of the page to start browsing from.