Predicting Positive and Negative Links in Online Social Networks
published: May 17, 2010, recorded: April 2010, views: 1314
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
We study online social networks in which relationships can be both positive (indicating friendship) and negative (indicating 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. Despite the diversity of settings considered, we find that the signs of links in the underlying social networks can be predicted with high accuracy using models that generalize across the different domains. These models provide insight into some of the fundamental principles that drive the formation of signed links in networks, and also shed light on theories of balance and status from social psychology.
Download slides: www2010_leskovec_ppn_01.pdf (2.7 MB)
Download slides: www2010_leskovec_ppn_01.ppt (4.1 MB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !