Dr Olivia Brown, associate Professor in Digital Futures, discusses her CREST research 'Online Signals of Extremist Mobilisation', which analyses the online behaviours of individuals who mobilised to right-wing extremist action.
Video created by the University of Bath.
TRANSCRIPT:
"We know that there's an enormous amount of extremist content online and trying to identify which actors and which content is most harmful is like trying to find a needle in a haystack.
What we're trying to do with this research is make the haystack smaller and the needles bigger.
We know from many years of research that there are a lot of people that radicalise online. However, there are very few people who actually go on to take part in terrorist action. We refer to this as mobilisation.
In this study, we were able to obtain a sample of social media posts from convicted right-wing extremists and non-convicted right-wing extremists and what we were able to do is, by comparing the social media posts,
try and identify signals of risk within online data that can help us to understand when an individual might be likely to go on when an individual might be likely to go on and take part in terrorist action.
Interestingly, while we had expected to find ideological and hateful content to be an important predictor of conviction status, what we actually found was that content in relation to operations, planning, logistics, longer posts and increased punctuation were actually all hallmarks of our convicted sample.
Obviously these models are never designed to be used in isolation and we would urge caution in how they're applied.
They should always be combined with other resources, other tools and other pieces of information.
There is a large body of literature on radicalisation.
We know a lot about how people become motivated to engage in terrorist action, but we know a lot less about the kind of mobilisation process itself."
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Video created by the University of Bath.