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Going Overboard: How Ironic Group Style Becomes Political on an Anonymous Imageboard

机译:过世:如何在匿名镜板上成为讽刺群体的政治

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Anonymous online groups such as imageboards have increasing cultural influence. Recently, they have been connected with far-right political movements. This mixed-methods study investigates politics on Overboard, a Finnish imageboard. We use a convolutional neural network to learn linguistic features of the community’s own understanding of politics, studying two large text corpora, collected in 2014–2015 and 2018–2019. This enables us to find political messages in nominally non-political subforums and discount non-political “noise”—finding the “needles in the haystack.” We quantify the prevalence of political talk on Overboard, assess its themes using topic modeling, and evaluate changes in their popularity. Finally, we qualitatively analyze the style of Overboard. We find that around one-tenth of messages on Overboard are identifiable as “political.” Often, but not univocally, they voice far-right opinions, usually somewhat ironically. The prevalence of far-right themes has increased, likely because of importing global imageboard culture and in parallel with the increased popularity of nationalist-right politics in the broader Finnish public sphere. In terms of group style, the strong boundary between members and outsiders, together with the ironic and cynical speech norms, creates a bond between members. Such a group style lends itself to politicizing the collective.
机译:匿名在线群体等摄像头具有越来越多的文化影响力。最近,他们已与远方的政治运动有关。这种混合方法研究研究了芬兰镜板的政治。我们使用卷积神经网络来学习社区对政治的理解的语言特征,研究了2014-2015和2018-2019收集的两个大型文本语料。这使我们能够在名义上的非政治子责任中找到政治信息,并折扣非政治“噪音” - 挑战干草堆的针头。“我们量化了对整个内容的政治谈判的普遍存在,使用主题建模评估其主题,并评估他们受欢迎程度的变化。最后,我们定性地分析了船体的风格。我们发现围绕船块的十分之一消息是可识别的“政治”。通常,但不是无周,他们的声音正确的意见,通常有些讽刺意味。最重要的主题的普遍性增加了,可能是因为进口全球摄影板文化,并与广泛的芬兰公共领域的民族主义政治的普及增加了平行。就集团风格而言,成员和外人之间的强界与讽刺和愤世嫉俗的语音规范一起创造了成员之间的债券。这样的团体风格为政治化了集体。

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