Understanding the Complexity of Business Information Dissemination in Social Media: A Meta‐Analysis of Empirical Evidence from China

中国 社会化媒体 荟萃分析 计算机科学 经验证据 信息传播 传播 数据科学 万维网 政治学 电信 医学 哲学 认识论 法学 内科学
作者
Jiawen Yan,Yuantao You,Yu Wang,Dongfang Sheng
出处
期刊:Complexity [Hindawi Limited]
卷期号:2021 (1) 被引量:6
标识
DOI:10.1155/2021/7647718
摘要

With the development of social networks, the complexity of the factors affecting the users’ information dissemination is increasing and the complexity of online social networks and influencing factors of individual behaviors and attitudes make the development of online public opinion present a dynamic, complex, and multifactor evolution. Analyzing the influencing factors of public opinion dissemination is conducive to optimize company management and information diffusion management. However, there has been no comprehensive analysis of the complex factors that influence the dissemination of information; this study focused on synthesizing 20 empirical studies on the influencing factors of China public opinion dissemination from the perspective of the user, and a meta‐analysis was conducted. We establish the influencing factors of users’ information adoption model from three aspects of information source reliability, perceived information quality, and the heat of public opinion events based on elaboration likelihood model. The results indicated that the main influencing factors of public opinion communication are authority, reliability, quality of information form, quality of information editing, quality of information utility, and event attendance preference. Among the factors, authority and quality of information editing have more significant impacts on users’ information adoption behavior in the dissemination of public opinion. In addition, whether the type of event was a public emergency had a moderating effect. The results are helpful to explore the universality of the influencing factors so as to help related regulators better build a multiangle supervision mechanism and conduct early warning of information diffusion.

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