Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Microscopic evolution of social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining interesting link formation rules in social networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Predicting recent links in FOAF networks
SBP'12 Proceedings of the 5th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
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Online social networks are dynamic in nature. While links between users are seemingly formed and removed randomly, there exists some interested link formation behaviors demonstrated by users performing link creation and removal activities. Uncovering these behaviors not only allows us to gain deep insights of the users, but also pave the way to decipher how social links are formed. In this paper, we propose a general framework to define user link formation behaviors using well studied local link structures (i.e., triads and dyads) in a dynamic social network where links are formed at different timestamps. Depending on the role a user plays in a link structure, we derive different types of link formation behaviors. We develop models for these behaviors and measure them for a set of users in an Epinions dataset.