TY - JOUR
T1 - Islamophobes are not all the same! A study of far right actors on Twitter
AU - Vidgen, Bertie
AU - Yasseri, Taha
AU - Margetts, Helen
N1 - Publisher Copyright:
© 2021 Department of Security Studies and Criminology.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Far-right
KW - hate speech
KW - Islamophobia
KW - online abuse
KW - social media
UR - http://www.scopus.com/inward/record.url?scp=85101915680&partnerID=8YFLogxK
U2 - 10.1080/18335330.2021.1892166
DO - 10.1080/18335330.2021.1892166
M3 - Article
AN - SCOPUS:85101915680
SN - 1833-5330
VL - 17
SP - 1
EP - 23
JO - Journal of Policing, Intelligence and Counter Terrorism
JF - Journal of Policing, Intelligence and Counter Terrorism
IS - 1
ER -