Exploring information dissemination effect on social media: an empirical investigation.

Abstract

Operators make profits by publishing information. If they can know the influencing factors in the process of information dissemination, they can provide new insights for practical operations and formulate corresponding operation strategies for different types of accounts. The purpose of this article is to discuss the information dissemination process of WeChat public accounts and what factors will affect the reading rate and sharing rate of the article. In this paper, the "feedback-sympathize-identify participant-share" (FSIPS) two-stage model is used to analyze the characteristics of information dissemination, and the negative binomial regression model is used to analyze which factors have a significant impact on the two stages of the dissemination model. Our data is obtained from a company that specializes in operating WeChat Official Accounts, and the data is authentic and more valuable. We collectively consider the roles of users, message content, interactions between content and individuals, and the context of social media in information dissemination behaviors (i.e., reading and sharing). In this process, some new variables, such as environment-related variables, are involved and incorporated into the two stages of information dissemination for analysis. The results show that the like rate, which is one of the feedback dimensions, has the greatest impact on the reading rate, while the favorite rate has the greatest impact on the sharing rate. Article type also plays a crucial role in the dissemination of information. In addition, the content relevance between the title and the content also largely affects the share rates of the three types.