Understanding the Causes and Consequences of Online Hate Speech in News Comments

Georgia Kernell and Seonhye Noh

This study examines the causes and consequences of online hate speech by systematically analyzing comments on one of the largest online news platforms in the world. Our study creates a novel, online news participation-tracking dataset using Naver News, the largest news-aggregating service in South Korea.

We analyze the content of comments on Naver to compare the networks of communication among those who engage in hate speech with those who do not. Using the natural experiment of when Naver introduced Cleanbot, we can examine how regulations that flag inflammatory comments causally impact hate speech and news consumption more generally. In addition, we are working to compare hate speech with news content and major events in Korea. To this end, we ask: does hate speech lead or lag (or both) hate crimes? Hate crimes have become increasingly common in Korea over the past decade, and it is an important context to better understand these connections.