Influence Maximization in Social Networks When Negative Opinions May Emerge and Propagate

• Published in: Society for Industrial and Applied Mathematics. Proceedings of the SIAM International Conference on Data Mining p. 379
• Main Authors: Chen, Wei, Collins, Alex, Cummings, Rachel, Ke, Te, Liu, Zhenming, Rincon, David, Sun, Xiaorui, Wang, Yajun, Wei, Wei, Yuan, Yifei
• Format: Conference Proceeding
• Language: English
• Published: Philadelphia Society for Industrial and Applied Mathematics 01.01.2011
• Subjects: Algorithms; Approximation; Heuristic; Influence; Opinions; Simulation; Social networks; Studies

Influence maximization, defined by Kempe, Kleinberg, and Tardos (2003), is the problem of finding a small set of seed nodes in a social network that maximizes the spread of influence under certain influence cascade models. In this paper, the researchers propose an extension to the independent cascad...