Research On The Knowledge Contribution Intention In Q&A Communities Based On Hidden Markov Model

With the rapid development of Internet and information technology, network application changed the way,where people access information, share knowledge, and communicate with others. In recent years, the popularity of Web2.0 technology makes the network information chang ed from the original one-way relationship to the network relationship, which emphasized the user-centric, social cooperation and shared community. The Q&A community is one of the typical application in the social network virtual community. It gets rid of the shortcomings of traditional quiz platform, and fully reflects the user-centered and socialoriented philosophy.Knowledge contribution is a user-centric behavior in the Q&A community users by answering, exchange and discussion, which achieves the sharing of knowledge and dissemination of information, so as to promote the positive development of the entire Q&A community. In previous studies, they majored in the basic concept of Q&A community, and motivation elaborate patterns and user behavior knowledge contribution. There is not a complete theoretical system and research methods. Therefore, we use classical Hidden Markov Model of latent class analysis to study the potential knowledge contribution intention and the factors in the Q&A community.First, on the basis of existing research re sults, this study cited social exchange theory, social learning theory and social capital the ory as the theoretical support. We summarize the factors affecting the intention to change user ’ knowledge contribution. Secondly, we explain the applicability of Hidden Markov model for the research questions. and set the function of each part of the model that can be suitable for this study in order to establish a theoretical model. Finally, we select the Zhihu user data as the data sample and make empirical analysis with the proposed model. We implemented a potential classification method for Zhihu based on the knowledge contribution intention, and explain the variation and factors of knowledge contribution intention, and made operational recommendations combined with practical experience.