Text Mining Model for Virtual Community User Portrait Based on Social Network Analysis

Abstract

With the rapid development of virtual communities, more and more customers participate in product innovation and knowledge sharing through virtual communities. Research on virtual community members, especially for community members, will help the community to manage the members and further promote community development and knowledge innovation. At present, the main difficulty in the study of community member user portraits lies in the user's grasp of user behavior data in the community. There is a large amount of structured data and semi-structured data in the community, which is crucial for the portrayal dimension of user portraits. This paper uses the association rule crawler algorithm to conduct community user behavior data association search, and uses text mining, social network analysis (SNA) and clustering technology to image users in the knowledge innovation community from the perspectives of professionalism, participation enthusiasm and network capability. The main result divides users into fancier, participator, and tourist.