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Measuring Polarization in Twitter Enabled in Online Political Conversation: The Case of 2016 US Presidential Election

机译:测量在线政治对话中Twitter的两极分化:以2016年美国总统大选为例

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Political Polarization is the divergence of attitudes toward ideological extremes and it is more likely to happen in groups of like-minded individuals. We measured polarization on Twitter during the 2016 United States Presidential elections, analyzing Twitter backchanneling conversations occurring during the three Presidential debates. The polarization metric we use is based on an existing metaphor of the electric dipole. In each debate the polarization dynamic followed a U-shaped pattern, with polarization being high at the beginning of the debate, decreasing over time, and finally bouncing back to a value that was higher than the initial one. The temporary decline of polarization is due to the increase in interaction with participants holding opposite opinions, but apparently this interaction is more conducive to confrontation than to revision of existing beliefs. We argue that the characteristics of Twitter are generally conducive to polarized and manipulable online debate.
机译:政治两极分化是对极端意识形态的态度分歧,更有可能在志同道合的个人群体中发生。我们在2016年美国总统大选期间测量了Twitter上的两极分化,分析了在三场总统辩论中发生的Twitter回传对话。我们使用的极化度量基于电偶极子的现有隐喻。在每次辩论中,极化动态都遵循U形模式,在辩论开始时极化强度很高,随着时间的流逝逐渐减小,最后反弹到一个高于初始值的值。两极分化的暂时性下降是由于与持相反意见的参与者之间的互动增加,但显然这种互动更有利于对抗,而不是对现有信念的修正。我们认为,Twitter的特征通常有利于两极化和可操纵的在线辩论。

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