Evaluating similarity measures: a large-scale study in the orkut social network
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Follow the (slash) dot: effects of feedback on new members in an online community
GROUP '05 Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work
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 game theoretical approach to broadcast information diffusion in social networks
Proceedings of the 44th Annual Simulation Symposium
Sharing News Articles Using 140 Characters: A Diffusion Analysis on Twitter
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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One major function of social networks (e.g., massive online social networks) is the dissemination of information such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to a receiver intrinsically involves both of them considering their self-perceived knowledge, reputation, and popularity, which further determine their decisions of whether or not to forward the information and whether or not to provide feedback. To understand such human aspects of the information dissemination, we propose a game theoretical model of the two-way full duplex information for-warding and feedback mechanisms in a social network that take into account the personalities of the communicating actors (including their perceived knowledgeability, reputation, and desire for popularity) and the global characteristics of the network. The model demonstrates how the emergence of social networks can be explained in terms of maximizing game theoretical utility.