SNS (social networking services) is a significant platform for Internet users to get knowledge and information , and users can share messages mutually via this platform. This kind of sharing can make user exchanges and gain useful information to benefit themselves. However, in recent years, the crisis of stickness has appeared in SNS, which raised the attention of the social network industry. Relevant professionals explain that most users may gradually reduce the interest of sharing knowledge on SNS websites and applications and then give it up because the platforms utilize simple and uninterested methods to attract the users to participate actively on them. But factors influencing the knowledge sharing on SNS websites and applications should be identified clearly through researches. Sina Weibo is one of the largest SNS platforms in the world, and the researches on the factors influencing the knowledge sharing of users could be valuable for the issue. This paper establishes the theoretical analysis model of knowledge sharing in SNS sites and applications, analyzes the influencing factors of knowledge sharing on them, and puts forward the corresponding strategies thereof. With the questionnaire surveys of Sina Weibo users, this article will discuss the influencing factors of knowledge sharing, and analyze the influencing factors on social network site as well as improving the stickness of users, so as to achieve the aim that SNS platforms capable of expanding the mount of users. It will firstly discuss the theoretical foundations, from which the hypotheses are put for. After that, the method of the study is discussed. Finally, it would be concluded with the theoretical implications,practical implications, limitations, and future research opportunities. The results of this study could be helpful for researchers in understanding the underlying reasons for social network activities as well as for SNS developers in improving SNS services.
Lu, Jinku and Kim, Jong-Ki, "Which factors influence knowledge sharing in SNS? Sina Weibo for instance" (2016). PACIS 2016 Proceedings. 158.