Abstract
Social networks are usually made of users linked by friendship, which can be dependent on (or influenced by) user characteristics (e.g., connectivity, centrality, weight, importance, activity in the networks). Among many friends of these social network users, some friends are more diverse (e.g., more influential, prominent, and/or active in a wide range of domains) than other friends in the networks. Recognizing these diverse friends can provide valuable information for various real-life applications when analyzing and mining huge volumes of social network data. In this paper, we propose a tree-based mining algorithm that finds diverse friends, who are highly influential across multiple domains, in social networks.
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Tanbeer, S.K., Leung, C.KS. (2013). Finding Diverse Friends in Social Networks. In: Ishikawa, Y., Li, J., Wang, W., Zhang, R., Zhang, W. (eds) Web Technologies and Applications. APWeb 2013. Lecture Notes in Computer Science, vol 7808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37401-2_31
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DOI: https://doi.org/10.1007/978-3-642-37401-2_31
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