Analyzing the Targets of Hate in Online Social Media

TL;DR

This paper presents a large-scale analysis of hate speech targets on social media, using data from Whisper and Twitter to identify hate speech forms and inform prevention strategies.

Contribution

It introduces a novel methodology for detecting hate speech across different social media platforms and provides the first comprehensive measurement of hate speech targets.

Findings

Identified main targets of hate speech on social media

Developed validated detection methodology

Provided insights for hate speech prevention

Abstract

Social media systems allow Internet users a congenial platform to freely express their thoughts and opinions. Although this property represents incredible and unique communication opportunities, it also brings along important challenges. Online hate speech is an archetypal example of such challenges. Despite its magnitude and scale, there is a significant gap in understanding the nature of hate speech on social media. In this paper, we provide the first of a kind systematic large scale measurement study of the main targets of hate speech in online social media. To do that, we gather traces from two social media systems: Whisper and Twitter. We then develop and validate a methodology to identify hate speech on both these systems. Our results identify online hate speech forms and offer a broader understanding of the phenomenon, providing directions for prevention and detection approaches.