Monitoring the Sources, Targets and Intensity of Hate Speech in the US Media

• In Event: Ingroups and Outgroups in the News

Abstract

Hate speech blaming out-groups for the perceived problems of, and threats against, the in-group is often at the heart of populist rhetoric. While much communication research today focuses on social media, the mass media within most Western states continues to be a leading source of news and act as a central disseminators of hate speech. But how can we find the sources and targets of hate speech within the mass media in a rigorous and objective manner? This article
is based on a research project that aims to create an objective accounting of hate speech within the US media landscape by identifying the sources, targets and intensity of hate speech in leading US media political talk/news shows, focusing initially on the top 10 conservative and top 10 liberal shows by audience size across radio, cable news and YouTube. The study uses a Python-based keyword extraction method to identify potential cases of hate speech, which are then validated by human coders on a novel 6-point hate speech intensity scale. Keywords are based on finding co-located words from two dictionaries – one based on negative words (approx. 6,000 words) and the other on groups (approx. 300 groups). This study examines the 7-day period before and after the 2018 US Midterm elections on November 6, 2018, which generated over 20,000 system-derived units of analysis.

Author

• Babak Bahador, George Washington University