Mining interesting link formation rules in social networks

Link structures are important patterns one looks out for when modeling and analyzing social networks. In this paper, we propose the task of mining interesting Link Formation rules (LF-rules) containing link structures known as Link Formation patterns (LF-patterns). LF-patterns capture various dyadic and/or triadic structures among groups of nodes, while LF-rules capture the formation of a new link from a focal node to another node as a postcondition of existing connections between the two nodes. We devise a novel LF-rule mining algorithm, known as LFR-Miner, based on frequent subgraph mining for our task. In addition to using a support-confidence framework for measuring the frequency and significance of LF-rules, we introduce the notion of expected support to account for the extent to which LFrules exist in a social network by chance. Specifically, only LF-rules with higher-than-expected support are considered interesting. We conduct empirical studies on two real-world social netwo...

• Type: Journal
• Year: 2010
• Where: CIKM
• Authors: Cane Wing-ki Leung, Ee-Peng Lim, David Lo, Jianshu Weng
• Keywords: CIKM 2010, Frequent Subgraph Mining, Information Technology, Link, Social Network