Deeply-held group beliefs can motivate people to engage in hate crimes. Yet predicting these crimes is extremely challenging because of their statistical rarity. This project uses computational methods and big data from social media to predict when virulent hate speech transitions to hate crimes. The research examines how the language of hateful speech and its dissemination over social networks predicts hate crimes. The scientific goal is to inform and advance theory and basic understanding of the social and cognitive processes that underlie extreme and hateful thoughts and how they spread. One aim is to identify mechanisms that might inhibit the dissemination of hate speech in social media. Another is to provide new tools for law enforcement. Students and faculty across many disciplines will have an opportunity to learn new computational methods for handling big data and for examining the spread of ideas online and through social media.
By integrating theories of social cognition with natural language processing and machine learning techniques, this project seeks to understand how deeply-held beliefs and identity dynamics coalesce to form extreme perspectives that could result in derogation of out-groups and hate crimes. It examines the linguistic features that characterize certain forms of social cognition and hate speech, and considers how the spatial distribution of hate speech can be estimated from sparse, biased data. The research considers whether socially-motivated hate crimes and acts of hate speech can be predicted using unobtrusive measures and information about social networks. The related educational and training opportunities include mentoring of students from minority-serving institutions, sharing newly-developed tools for text analysis with the wider scientific community, and workshops on machine learning and text analysis. This CAREER award is supported jointly by the NSF Social Psychology and Secure and Trustworthy Cyberspace (SaTC) Programs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
