Islamophobes are not all the same! A study of far right actors on Twitter

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.

KEYWORDS:

• Far-right
• Islamophobia
• hate speech
• online abuse
• social media

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available at https://zenodo.org/record/3701589#.YDTZfhP7SUo.

Notes

1 We provide the IDs of the 5.2 million tweet data set at: https://zenodo.org/record/3701589#.YDTZfhP7SUo.

2 We repeat all of our analyses on the full data set, without any users removed for high volume tweeting, and find similar results.

3 The average of 89% for ‘None’ is lower than the value reported in Figure 1(a).

Additional information

Funding

This work was supported by Economic and Social Research Council [grant number ES/J500112/1].