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We are using a complex systems approach in a pilot project to create a data-driven real-time empirical analysis of the self-radicalisation phenomenon. The project, if successful, will generate actionable predictions about the likelihood that particular individuals of interest will become self-radicalised. In the pilot project, we use validated open source data to empirically test three hypotheses: individuals reveal their ‘identity’ – a personal signature – through their texts; there exist tipping-point phenomena where ‘identity’ may shift rapidly from one metastable state to another; and an individual's ‘identity’ will show critical slowing down – the characteristic dynamics that predict the approach of a tipping point.
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