This paper addresses several of the key issues facing creation of a classifier for hate-speech on forums, blogs, or other areas of web discourse.
This article deals with a supervised machine learning text classifier, trained and tested to distinguish between hateful and/or antagonistic response with a focus on race, ethnicity or religion; and more general responses.
This source pertains to the method by which extreme right and hate groups take advantage of user-generated video content websites’ recommender systems to pander to wider, more susceptible audiences.
This background note pertains to how far right extremist groups have coopted methods from the ‘cyber caliphate’ and jihadist Internet use to develop their own support networks.
This report analyzes over one hundred cases from 2010 through 2012 as it describes the various stages that far right movements move through, from peddling hate online to violence and death on the streets.
This report was issued two weeks before the largest trial on far-right extremism in German history opened in Munich.
This article studied a selection of right-wing extremist (RWE) groups on Twitter. The authors looked at particular language-based networks as case studies, collecting Twitter data for groups across eight countries.
This portal gathers an annotated collection of recent research on the ways in which social media and new technologies may be leveraged in the fight against violent extremism