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论文编号：	11961
作者编号：	2120183092
上传时间：	2020/12/7 21:39:56
中文题目：	网络虚拟社区用户参与行为的影响因素研究 ——以知乎为例
英文题目：	Research on Influencing Factors of User Participation Behavior in Virtual Community: The case of zhihu
指导老师：	李月琳
中文关键字：	网络虚拟社区；问答社区；人格特质；动机；信息行为
英文关键字：	Virtual community,Q&A community,Personality traits,Motivation,Information behavior
中文摘要：	随着数字化应用的普及，网络虚拟社区成为了互联网用户搜索和分享信息的重要场所。虚拟社区中的用户和内容是平台能够健康、长久发展的主要影响因素。本研究选取具有知识属性和社交属性的知乎平台作为研究对象，探究用户在虚拟社区中参与行为的影响因素，进而从用户层面探讨如何保持虚拟社区用户活跃度、提高用户粘性，寻求保持社区竞争优势的方法。 本研究从用户个人层面出发，结合使用与满足理论、动机理论，借鉴网络用户信息交互行为理论框架以及虚拟社区信息行为等相关研究，构建了知乎社区用户参与行为模型。该模型分别从用户的人格特质、参与信息活动的动机角度分析了显著影响用户参与行为的个人层面相关驱动因素。 经过理论探究和实证量化分析，得到如下结论：（1）知乎用户的参与维度可以划分为如下三个层面：浏览式参与、表达式参与和共享式参与。各个维度分别体现了用户在社区中的参与深度，反映出用户对于社区中信息的贡献程度。（2）不同的人格倾向以及不同动机表现出不同程度的参与方式。高外倾性人格特质和信息动机对用户的参与行为存在显著的正向影响；除此之外，开放性和尽责性人格特质、娱乐动机和情感动机也对浏览式参与行为产生显著的正向影响；外倾性、宜人性人格特质以及社交动机和情感动机对表达式参与行为有显著的正向影响；自我实现、社交和情感动机以及神经质、外倾性和开放性人格特质倾向对共享式参与行为呈现显著的影响，其中高神经质性人格特质与共享式参与行为之间是显著的负相关关系，其余为正向相关关系。 最后，根据分析结果，分别从用户、社区、内容运营三个方面出发，为知乎社区的健康且可持续发展提出了合理化建议：第一，按信息参与水平划分用户类型，采取相应运营策略，提高社群稳定性；第二，识别用户人格特质倾向和动机，从用户需求角度出发完善社群运营策略。第三，利用人格特质和动机特点，辅助社区内容建设，提高社区信息质量。
英文摘要：	With the popularity of digital applications, the network virtual community has become an important place for Internet users to search and share information. The users and content of virtual community are the main influencing factors for the healthy and long-term development of the platform. In this study, Zhihu platform with knowledge attributes and social attributes is selected as the research object to explore the influencing factors of users participation behavior in virtual community, and then to explore how to maintain the activity of users in virtual community, improve user stickiness and find ways to maintain the competitive advantage of the community from the user level. Based on the personal level of users, combined with the theory of usage and satisfaction, motivation theory, drawing lessons from the theoretical framework of network user information interaction behavior and virtual community information behavior and other related research, this study constructs the user participation behavior model of Zhihu community. The model analyzes the personal drivers that significantly affect the users participation behavior from the perspective of users personality traits and the motivation to participate in information activities. Through theoretical research and empirical quantitative analysis, the following conclusions are drawn: (1) the dimension of Zhihu users participation can be divided into the following three levels: browsing participation, expression participation and shared participation. Each dimension reflects the depth of user participation in the community and the degree of contribution of users to the information in the community. (2) different personality tendencies and different motivations show different degrees of participation. High extroversion personality traits and information motivation have significant positive effects on users participation behavior; in addition, openness and due diligence personality traits, entertainment motivation and emotional motivation also have significant positive effects on browsing participation behavior; extroversion, agreeable personality traits, social motivation and emotional motivation have significant positive effects on expression participation behavior. Self-realization, social and emotional motivation, neuroticism, extroversion and open personality traits had significant effects on shared participation behavior, in which there was a significant negative correlation between high neuroticism personality traits and shared participation behavior, while the rest were positive correlation. Finally, based on the analysis results, reasonable Suggestions are put forward for the healthy and sustainable development of Zhihu community from three aspects, namely, users, community and content operation. First, users are divided according to the level of information participation, and corresponding operation strategies are adopted to improve the stability of the community.Second, identify users' personality traits and motivations, and improve community operation strategies from the perspective of user needs.Third, the use of personality and motivation characteristics, to assist the construction of community content, improve the quality of community information.
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