Social community detection and message propagation scheme based on personal willingness in social network

Personal willingness is one of the most important factors influencing the construction of social community and the message propagation in social network. Personal willingness is used to describe the subjective initiative of node (user) to communicate information with outside world. The personal willingness is greater, the corresponding user is more willing to make communication with outside world, then the user is more likely to join the corresponding community. So, personal willingness may reduce the probability of generating large-scale communities so as to improve the accuracy and reliability of community detection and increase the stability of community structure. This paper proposes a social community detection and message propagation scheme based on personal willingness in social network. In the proposed scheme, the social community detection algorithm extracts node attributes and then uses modularity degree, interest degree and personal willingness to sophisticatedly detect social communities; also, the message propagation method is based on the exponential model, which constructs feature vector by edge feature and node feature, willingness vector by personal willingness and community willingness, and related basic relationship by propagation probability and propagation delay. Based on the Weibo, YouTube and Digg data, the experiments show that our proposed scheme can ensure the stability and reliability of social community detection and add the initiative and effectiveness of message propagation among users.