Automatic Detection of Hate Speech on Facebook Using Sentiment and Emotion Analysis

Hate speech has been an issue since the start of the Internet, but the advent of social media has brought it to unimaginable heights. To address such an important issue, in this paper, we explore a novel framework to effectively detect highly discussed topics that generate hate speech on Facebook. With the use of graph, sentiment, and emotion analysis techniques, we cluster and analyze posts on prominent Facebook pages. Consequently, the proposed framework is able to identify the pages that promote hate speech in the comment sections regarding sensitive topics automatically.