Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Influence and correlation in social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Feedback effects between similarity and social influence in online communities
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
Mining topic-level influence in heterogeneous networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Understanding retweeting behaviors in social networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Topic-based PageRank on author cocitation networks
Journal of the American Society for Information Science and Technology
Proceedings of the 20th international conference on World wide web
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Social influence in social networks has been extensively researched. Most studies have focused on direct influence, while another interesting question can be raised as whether indirect influence exists between two users who're not directly connected in the network and what affects such influence. In addition, the theory of complex contagion tells us that more spreaders will enhance the indirect influence between two users. Our observation of intensity of indirect influence, propagated by n parallel spreaders and quantified by retweeting probability in two Twitter social networks, shows that complex contagion is validated globally but is violated locally. In other words, the retweeting probability increases non-monotonically with some local drops. A quantum cognition based probabilistic model is proposed to account for these local drops.