Decoding Hate: Using Experimental Text Analysis to Classify Terrorist Content

This paper uses automated text analysis – the process by which unstructured text is extracted, organised and processed into a meaningful format – to develop tools capable of analysing
Islamic State (IS) propaganda at scale. Although we have used a static archive of IS material, the underlying principle is that these techniques can be deployed against content produced by any number of violent extremist movements in real‑time. This study therefore aims to complement work that looks at technology‑driven strategies employed by social media, video‑hosting and file‑sharing platforms to tackle violent extremist content disseminators.