Abstract
With the advance of high techniques, more and more connections between individuals in a social network can be identified, but it is still hard to obtain the complete relation information between individuals for complex structure and individual privacy. However, the social networks have communities. In our work, we aim at mining the invisible or missing relations between individuals within a community in social networks. We propose our algorithm according to the fact that the individuals exist in communities satisfying Nash Equilibrium, which is borrowed from game-theoretic concepts often used in economic researches. Each hidden relation is explored through the individual’s loyalty to their community. To the best of our knowledge, this is the first work that studies the problem of mining hidden links from the aspect of Nash Equilibrium. Eventually we confirm the superiority of our approach from extensive experiments over real-world social networks.
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Ma, H., Lu, Z., Fan, L., Wu, W., Li, D., Zhu, Y. (2013). A Nash Equilibrium Based Algorithm for Mining Hidden Links in Social Networks. In: Widmayer, P., Xu, Y., Zhu, B. (eds) Combinatorial Optimization and Applications. COCOA 2013. Lecture Notes in Computer Science, vol 8287. Springer, Cham. https://doi.org/10.1007/978-3-319-03780-6_13
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DOI: https://doi.org/10.1007/978-3-319-03780-6_13
Publisher Name: Springer, Cham
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