Comparing Social Media Communities using Functional Data Analysis

利用功能数据分析比较社交媒体社区

阅读:1

Abstract

Various social media communities can lead conversations in entirely divergent directions, shaping the nature of information shared on these platforms. Deliberate disinformation and manipulated messages, disseminated both within and beyond these communities, hold the potential to reshape public opinion on a broader scale. A constructive analysis that delves into the disparities between these opposing groups could prove invaluable in discerning the pathways through which information flows. Our research examines the temporal dynamics of social media groups, assessing their behavior through metrics such as time dependent post and retweets. Using functional data analysis, we investigate Tweets related to incidents like the Skripal/Novichok case and the Bucha Crimes. Our goal is to quantify the disparities between these communities and uncover the strategies employed by each group to promote specific campaigns. Our preliminary findings shed new light on the mechanics of information dissemination, offering insights that may inform decisions about optimal response times.

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。