基于的推特回声室的探测
Manuel Pratelli1,2, Fabio Saracco3,1,4, Marinella Petrocchi2,1
1IMT School For Advanced Studies Lucca, Piazza San Francesco 19, Lucca 55100, Italy.
PNAS nexus
|May 13, 2024
概括
我们开发了一种基于无偏的方法来检测回声室. 我们的研究发现,回声室的存在有限,但对言论产生了重大影响,并且在意大利的Covid-19疫苗接种辩论中与错误信息有关.
科学领域:
- 社交媒体分析 社交媒体分析
- 计算社会科学 计算社会科学
- 信息科学 信息科学 信息科学
背景情况:
- 用户遇到与先前信念一致的信息的回声室在在线讨论中很普遍.
- 了解它们的形成和影响对于分析在线话语和信息传播至关重要.
研究的目的:
- 引入一种基于的新,无偏见的方法来检测回声室.
- 量化回声室在意大利Twitter辩论中对Covid-19疫苗接种的存在和影响.
主要方法:
- 开发一种数据不可知,基于的算法,用于回声室检测.
- 该方法应用于关于COVID-19疫苗接种的意大利Twitter辩论的数据集.
主要成果:
- 在回声室内观察到使用者的流行率较低 (约为0.35%).
- 尽管数字很低,但回声室用户显著影响了话语,占所有转发的近三分之一.
- 在这种情况下,回声室似乎是虚假信息的重要来源.
结论:
- 拟议的基于的方法提供了一个不偏见的方法来识别回声室.
- 即使是小的回声室也可以不成比例地影响在线话语,并可能放大错误信息,就像在Covid-19疫苗接种辩论中看到的那样.
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