消极性传播得更快:对政治传播中情绪作用的大规模多语种twitter分析

Q1 Social Sciences Online Social Networks and Media Pub Date : 2023-01-01 DOI:10.1016/j.osnem.2023.100242
Dimosthenis Antypas, Alun Preece, Jose Camacho-Collados
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引用次数: 4

摘要

在现代社会的政策制定中,社交媒体已经变得极具影响力,尤其是在西方世界,推特等平台允许用户关注政客,从而使公民更多地参与政治讨论。同样,政客们使用推特表达自己的观点,就当前话题进行辩论,并宣传旨在影响选民行为的政治议程。在本文中,我们试图分析来自三个欧洲国家的政治家的推文,并探讨他们推文的病毒性。先前的研究表明,传达负面情绪的推文可能会被转发得更频繁。通过使用最先进的预先训练的语言模型,我们对从希腊、西班牙和英国议会议员(包括权力下放的政府)收集的数十万条推文进行了情绪分析。我们通过系统地探索和分析有影响力的推文和不太受欢迎的推文之间的差异来实现这一点。我们的分析表明,政客们的负面推文传播得更广,尤其是在最近的时代,并突出了政党之间以及政客和普通民众之间的有趣差异。
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Negativity spreads faster: A large-scale multilingual twitter analysis on the role of sentiment in political communication

Social media has become extremely influential when it comes to policy making in modern societies, especially in the western world, where platforms such as Twitter allow users to follow politicians, thus making citizens more involved in political discussion. In the same vein, politicians use Twitter to express their opinions, debate among others on current topics and promote their political agendas aiming to influence voter behaviour. In this paper, we attempt to analyse tweets of politicians from three European countries and explore the virality of their tweets. Previous studies have shown that tweets conveying negative sentiment are likely to be retweeted more frequently. By utilising state-of-the-art pre-trained language models, we performed sentiment analysis on hundreds of thousands of tweets collected from members of parliament in Greece, Spain and the United Kingdom, including devolved administrations. We achieved this by systematically exploring and analysing the differences between influential and less popular tweets. Our analysis indicates that politicians’ negatively charged tweets spread more widely, especially in more recent times, and highlights interesting differences between political parties as well as between politicians and the general population.

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来源期刊
Online Social Networks and Media
Online Social Networks and Media Social Sciences-Communication
CiteScore
10.60
自引率
0.00%
发文量
32
审稿时长
44 days
期刊最新文献
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