Islamophobes are not all the same! A study of far right actors on Twitter
Islamophobes are not all the same! A study of far right actors on Twitter
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伊斯兰恐惧症并不都是一样的！
DOI：
10.1080/18335330.2021.1892166
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发表时间：
2019
影响因子：
--
通讯作者：
H. Margetts
中科院分区：
文献类型：
--
作者：
Bertie Vidgen;T. Yasseri;H. Margetts
极右翼分子经常在网上散布仇视伊斯兰教的仇恨言论，利用社交媒体传播分裂和偏见的信息，这可能会引发群体间的紧张关系和冲突。仇恨内容可能对目标受害者造成伤害，在社区中造成恐惧感，并挑起群体间的紧张关系和冲突。因此，有迫切需要更好地了解在颗粒级如何伊斯兰恐惧症表现在线和谁生产它。我们调查了一个著名的英国极右政党在Twitter上，英国国家党的追随者之间的伊斯兰恐惧症的动态。通过分析一年内收集的500万条推文的新数据集，使用机器学习分类器和潜在马尔可夫模型，我们确定了七种类型的伊斯兰恐惧症极右翼行为者，捕捉了他们行为的定性，定量和时间差异。值得注意的是，我们表明，少数用户要为我们观察到的大多数伊斯兰恐惧症负责。然后，我们讨论了社会媒体监管的背景下，这种类型的政策含义。
ABSTRACT Far-right actors are often purveyors of Islamophobic hate speech online, using social media to spread divisive and prejudiced messages which can stir up intergroup tensions and conflict. Hateful content can inflict harm on targeted victims, create a sense of fear amongst communities and stir up intergroup tensions and conflict. Accordingly, there is a pressing need to better understand at a granular level how Islamophobia manifests online and who produces it. We investigate the dynamics of Islamophobia amongst followers of a prominent UK far right political party on Twitter, the British National Party. Analysing a new data set of five million tweets, collected over a period of one year, using a machine learning classifier and latent Markov modelling, we identify seven types of Islamophobic far right actors, capturing qualitative, quantitative and temporal differences in their behaviour. Notably, we show that a small number of users are responsible for most of the Islamophobia that we observe. We then discuss the policy implications of this typology in the context of social media regulation.
影响因子：
2.8
作者：
Burnap, Pete;Williams, Matthew L.;Voss, Alex
通讯作者：
Voss, Alex
永远是虚假的黎明？
影响因子：
1.2
作者：
Goodwin M
通讯作者：
Goodwin M