Research On The Quality Of Knowledge Contribution And Knowledge Interaction In Social Q&A Communities

With the rapid development of Web 2.0, as a representative of a new generation of social media, social Q&A communities provide users with a "question-answer" mechanism for information sharing, and gradually become an important way for Internet users to obtain information or knowledge. In Q&A communities, asking and answering are the two basic activities, and they are equally important because questions are the basis of answers and answers are the expression of user-generated content and the carrier of community knowledge and collective wisdom. With the popularization of the Internet, the problems of social Q&A communities have already shifted from insufficient information to information overload, people are increasingly concerned about the quality rather than the quantity of user-generated content.In this paper, we treat Zhihu as the research context, and use users’ behavior data to conduct the empirical researches from the perspectives of questions and answers respectively. We focus on two research questions that are related to the quality of usergenerated content in online communities: What kind of questions are easy to obtain highquality answers? What factors affect the quality of users’ answers? As the dependent variables are count variables, this paper uses a combination of Logit model, negative binomial regression model, zero-inflated negative binomial model and multiple regression model for empirical analysis. Firstly, we research the impact of the characteristics of questions, answers, askers and repliers on the quality of knowledge contribution from the perspective of answers. We find that social comparison, social exposure, identity-based trust, degree of specialization and image motivation have significant positive effects on the quality of answers. Secondly, we research the impact of the characteristics of questions and repliers on the quality of knowledge interaction from the perspective of questions. We find that the level of detail, the degree of attention, the number of topic tags, social presence, social status, the habit of cooperation and social exposure have significant positive effects on the number and the quality of the answers.This study covers the two main activities in social Q&A communities-- asking and answering. The results can guide knowledge seekers to obtain high-quality answers by asking reasonably, we also identify factors that influence the quality of users’ knowledge contribution, which covers the full picture of knowledge exchange in Q&A communities. If we reach the two targets described above, the widespread problem of false, distorted, obsolete and redundant information and many other issues can be effectively addressed. This research not only validate and enrich the theories in the fields of knowledge management, online communities behaviors and other related fields, but also can provide community managers and users with advice and reference when they make their decisions.