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作 者:杨奕[1] 张毅[1] Yang Yi;Zhang Yi(College of Public Administration,Huazhong University of Science and Technology,Wuhan 430074,China)
机构地区:[1]华中科技大学公共管理学院,湖北武汉430074
出 处:《现代情报》2021年第3期94-109,共16页Journal of Modern Information
基 金:国家社会科学基金重大项目“智慧社会下我国新型社会信用体系构建研究”(项目编号:19ZDA104);国家留学基金委“国家建设高水平大学公派研究生项目”(项目编号:202006160125)。
摘 要:[目的/意义]在信息技术快速发展的今天,社交媒体在复杂公共议题中承担了越来越重要的信息发布、用户参与和舆论引导功能。通过对社交媒体多平台的用户记录的大数据分析,可以考察跨国家和平台用户诉求的差异和传播途径。[方法/过程]基于中美贸易争端的现实案例,使用网络爬虫程序定时采集Twitter和Weibo的用户数据,应用概率主题分析、时间趋势分析、社会网络分析等大数据分析方法,剖析两大平台在议题分布、时间演化和关键影响者的表现形式与属性差异,尝试弥补现有研究体系视域的单一性问题。[结果/结论]结果表明:1)在网络环境中,现实事件对于用户行为和主题热度产生迅速的反映;2)引发平台主题框架差异的原因由特定的环境、制度或文化背景所塑造;3)关键影响者的类型和观点显著影响当地的议题讨论网络,并引导舆论走向。本研究实现了对社交媒体用户行为互动观察维度和理论维度的探索与推论,印证了跨平台差异的根本解释,在一定程度上回应理论与实践研究对社交媒体功能定位和发展优化的关注。[Purpose/Significance]With the rapid development of information technology today,social media has assumed more and more important functions of information release,user participation and opinion guidance in complex public issues.Through the big data analysis of user records on social media platforms,the differences in user demands and communication channels in cyberspace can be investigated.[Method/Process]Based on the reality of China-US Trade disputes case,the study used the web crawler Twitter and Weibo of user data.Then,it applied probability topic modeling,time trend analysis,and social network analysis,to explore the differences between the two platforms in the issue distribution,time evolution,and key influencers for trying to make up for the problem of unitary vision existing in the current research.[Result/Conclusion]The results showed that:(1)in the online environment,real events had a rapid impact on user behavior and topic popularity;(2)The reason that caused the difference of platform topic framework was shaped by specific environment,system or cultural background;(3)The types and opinions of key influencers significantly influenced the discussion network of the platform and guide the direction of public opinion.The study realized the exploration and inference of the interactive observation dimension and theoretical dimension of social media user behavior,verified the fundamental explanation of cross-platform factor differences,and responded to the social practice and theoretical research's attention to the function positioning and development optimization of social media to a certain extent.
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