Feature Selection Based on Audience´s Behavior for Information Filtering in Online Social Networks

Nowadays, online social networks (OSNs) become a part of human life. People use the OSNs for different purposes such as working, entertainment and so on. However, existing OSNs feed too much information into an audience´s social network page without recognized the audience´s situation or the audience´s desire. This problem, called information overload, is a weak point of current OSNs. Our ultimate goal is to change traditional feeding information used in existing OSNs to a new type of feeding information by filtering out inconsistent information with the audience´s situation. Therefore, this paper aims to prepare necessary features used in filtering information to get consistent information with the audience´s situation. We also study behavior of audience in several aspects by analysis characteristic of post. The result indicates that three features are essential for the audience´s decision to allow a post to be displayed on the audience´s social network page, which are n1 (topic of post), n0 (audience´s current situation), and n2 (type of relationship between audience and creator). Furthermore, other factors such as the number of times which a post is reviewed by the audience, age and, career have an impact on the audience´s decision.