Discovery of Opinion Leader Community Via Multilayer Structure based Time-dividing Approach

Abstract

With the advent of web 3.0, social network has become an important way to disclosure and spread the public sentiment. Opinion leaders play an important role in leading the direction of the public opinion. In this paper, due to the structure of the community in the network, we extracted the community by replies of each post in BBS, and we came up with an opinion leader community mining method based on level structure. In this way the communities each other have a better overlap result. Thus, communities can have more relations. Then, we analyzed the revolution of the communities after we got the structure of the opinion leader communities and we put forward a time-dividing method, and divided the whole communities into different pieces based on the character of the post and the duration of the time and we came up with the suitable measurement parameter to get the evolution result of the communities. Finally, experiments prove the efficiency of the opinion leader community mining method and we summarize the properties of the opinion leader community in revolution.

DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3349