Question Answering Community User Knowledge Sharing Behavior Research

The Q & A community has emerged as a social media and has become the main form of online Q&A.It provides an effective communication channel and communication method for the dissemination of today's network knowledge.Q&A community gathered users from different parts of the country who have different occupations and cultural backgrounds.The development of the community is inseparable from the user's search questions and questions.This article starts with the users of the question-and-answer community and uses content analysis methods,literature analysis methods,questionnaire survey methods,interview methods,and other research methods to combine the knowledge of journalism,communication,and social psychology to study the characteristics of user sharing.For the characteristic development of question-and-answer community,it provides suggestions for reference.The first chapter of this article first elaborates the background of Q & A community development and the significance of this study.It clarifies the definition of related concepts in Q & A community,and analyzes the status and characteristics of Q & A community in China.It divides the user's sharing behavior into responses,likes and forwards..The second chapter is about the overall research of Q & A community users' sharing behaviors,including the demographic characteristics of users,sharing motivations and influencing factors.It also analyzes in detail the user's achievement motivation,self-requirements,and the impact of personality characteristics on sharing behavior.The third chapter,the fourth chapter and the fifth chapter are the specific analysis of the users' responses,likes,and forwarding behaviors.The survey and judgment are conducted from both the users themselves and the characteristics of the text.At the same time,the analysis of the differences among these three sharing behaviors is summarized..The sixth chapter of this paper is the foothold of the study.With the goal of expanding the knowledge of question-and-answer community users,the community's optimization suggestions are proposed,including user groups,content forms,and management systems.