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理解推特上反移民情绪的蔓延。

Understanding anti-immigration sentiment spreading on Twitter.

机构信息

Department of Geography and Planning, Geographic Data Science Lab, University of Liverpool, Liverpool, United Kingdom.

出版信息

PLoS One. 2024 Sep 4;19(9):e0307917. doi: 10.1371/journal.pone.0307917. eCollection 2024.

Abstract

Immigration is one of the most salient topics in public debate. Social media heavily influences opinions on immigration, often sparking polarized debates and offline tensions. Studying 220,870 immigration-related tweets in the UK, we assessed the extent of polarization, key content creators and disseminators, and the speed of content dissemination. We identify a high degree of online polarization between pro and anti-immigration communities. We found that the anti-migration community is small but denser and more active than the pro-immigration community with the top 1% of users responsible for over 23% of anti-immigration tweets and 21% of retweets. We also discovered that anti-immigration content spreads also 1.66 times faster than pro-immigration messages and bots have minimal impact on content dissemination. Our findings suggest that identifying and tracking highly active users could curb anti-immigration sentiment, potentially easing social polarization and shaping broader societal attitudes toward migration.

摘要

移民是公共辩论中最突出的话题之一。社交媒体对移民问题的看法影响很大,经常引发两极分化的辩论和线下紧张局势。我们研究了英国 220870 条与移民相关的推文,评估了两极分化的程度、主要的内容创作者和传播者,以及内容传播的速度。我们发现,支持和反对移民的社区在网上存在高度分化。我们发现,反移民社区虽然规模较小,但比支持移民的社区更密集、更活跃,排名前 1%的用户发布的反移民推文占比超过 23%,转发量占比超过 21%。我们还发现,反移民内容的传播速度也比支持移民的信息快 1.66 倍,而且机器人对内容传播的影响微乎其微。我们的研究结果表明,识别和跟踪高度活跃的用户可能有助于抑制反移民情绪,从而有可能缓解社会两极分化,并塑造更广泛的社会对移民的态度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9279/11373840/ff64f05f697a/pone.0307917.g001.jpg

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