1. A Bootstrapped Model to Detect Abuse and Intent in White Supremacist Corpora
- Author
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Simons, B. and Skillicorn, D. B.
- Subjects
FOS: Computer and information sciences ,Computer Science - Computation and Language ,Computation and Language (cs.CL) - Abstract
Intelligence analysts face a difficult problem: distinguishing extremist rhetoric from potential extremist violence. Many are content to express abuse against some target group, but only a few indicate a willingness to engage in violence. We address this problem by building a predictive model for intent, bootstrapping from a seed set of intent words, and language templates expressing intent. We design both an n-gram and attention-based deep learner for intent and use them as colearners to improve both the basis for prediction and the predictions themselves. They converge to stable predictions in a few rounds. We merge predictions of intent with predictions of abusive language to detect posts that indicate a desire for violent action. We validate the predictions by comparing them to crowd-sourced labelling. The methodology can be applied to other linguistic properties for which a plausible starting point can be defined.
- Published
- 2020
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