Research on the dissemination of celebrities' opinions based on speech act theory and potential category analysis

基于言语行为理论和潜在类别分析的名人观点传播研究

阅读:2

Abstract

With the increasingly prominent role of social media in the timeliness and sharing of information dissemination, more and more research has focused on how to further improve user stickiness through social media. However, there is little consideration of the impact of celebrities' views on user behavior in social media. The main goal of this paper is to study the influence of celebrity language style on user communication and opinions dissemination. First, it analyzes the language style characteristics of celebrities' opinions and conducts cross-influence analysis between celebrity language style characteristics and user communication characteristics. Based on speech act theory, this study studies the influence of different language styles of celebrity Microblog on users' communication behavior and then builds a potential category analysis model to subdivide the views of celebrities. The results show that (1) Positive expression is the most common language style element combination of celebrities, and it also shows the most effective communication effect. This shows that users like to see celebrities show an active and positive side to the outside world, can analyze external things, and express their own opinions on these contents; (2) The combination of positive emotion, external attention, and analysis can produce the best communication effect; (3) The emotion of celebrities' opinions will affect the communication emotion of users to a certain extent, and the communication of users will have the development trend of reducing positive emotions and increasing negative emotions. Therefore, positive guidance and the dissemination of positive energy are more needed on public social platforms to minimize or avoid the dissemination of negative emotions.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。