Silent Signals, Loud Impact: LLMs for Word-Sense Disambiguation of Coded Dog Whistles

Anonymous

Abstract: A dog whistle is a form of coded communication with a secondary meaning that is often weaponized for racial discrimination. Dog whistles historically began in United States politics, but soon also took root in social media as a means of evading hate speech detection systems and maintaining plausible deniability. In this paper, we present an approach for word-sense disambiguation of dog whistles from standard speech using Large Language Models (LLMs), and leverage this technique to create a dataset of 11,570 high-confidence coded examples of dog whistles used in formal and informal communication. Silent Signals is the largest dataset of disambiguated dog whistle usage, created for applications in hate speech detection, neology, and political science.

Paper Type: long

Research Area: Computational Social Science and Cultural Analytics

Contribution Types: NLP engineering experiment, Data resources

Languages Studied: English