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Using sentiment analysis to define twitter political users’ classes and their homophily during the 2016 American presidential election
Journal of Internet Services and Applications Pub Date : 2018-09-03 , DOI: 10.1186/s13174-018-0089-0
Josemar A. Caetano , Hélder S. Lima , Mateus F. Santos , Humberto T. Marques-Neto

This paper proposes an analysis of political homophily among Twitter users during the 2016 American Presidential Election. We collected 4.9 million tweets of 18,450 users and their contact network from August 2016 to November 2016. We defined six user classes regarding their sentiment towards Donald Trump and Hillary Clinton: whatever, Trump supporter, Hillary supporter, positive, neutral, and negative. Next, we analyzed their political homophily in three scenarios. Firstly, we analyzed the Twitter follow, mention and retweet connections either unidirectional and reciprocal. In the second scenario, we analyzed multiplex connections, and in the third one, we analyzed friendships with similar speeches. Our results showed that negative users, users supporting Trump, and users supporting Hillary had homophily in all analyzed scenarios. We also found out that the homophily level increase when there are reciprocal connections, similar speeches, or multiplex connections.

中文翻译:

使用情绪分析来定义2016年美国总统大选期间Twitter政治用户的阶层及其同质性

本文提出了对2016年美国总统大选期间Twitter用户之间政治同质性的分析。从2016年8月到2016年11月,我们收集了490万条发推文,涉及18,450个用户及其联系网络。关于唐纳德·特朗普和希拉里·克林顿的情绪,我们定义了6个用户类别:任意,特朗普支持者,希拉里支持者,正面,中性和负面。接下来,我们在三种情况下分析了他们的政治同质性。首先,我们分析了Twitter的追踪,提及和转发单向和对等连接。在第二种情况下,我们分析了多路复用连接,在第三种情况下,我们分析了具有类似语音的友谊。我们的结果表明,在所有分析的场景中,负面用户,支持Trump的用户和支持Hillary的用户都是同质的。
更新日期:2018-09-03
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