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Interactive Mining of Strong Friends from Social Networks and Its Applications in E-Commerce
Authors:Syed K Tanbeer  Juan J Cameron
Institution:Department of Computer Science, University of Manitoba, Winnipeg, Manitoba, Canada
Abstract:Social networks are generally made of individuals who are linked by some types of interdependencies such as friendship. Most individuals in social networks have many linkages in terms of friends, connections, and/or followers. Among these linkages, some of them are stronger than others. For instance, some friends may be acquaintances of an individual, whereas others may be friends who care about him or her (e.g., who frequently post on his or her wall). In this study, we integrate data mining with social computing to form a social network mining algorithm, which helps the individual distinguish these strong friends from a large number of friends in a specific portion of the social networks in which he or she is interested. Moreover, our mining algorithm allows the individual to interactively change his or her mining parameters. Furthermore, we discuss applications of our social mining algorithm to organizational computing and e-commerce
Keywords:data mining  interactive mining  organizational computing  social computing  social computing applications  social media  social networks  social network analysis and mining
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