Monitoring Targeted Hate in Online Environments

TL;DR

This paper introduces a dictionary-based method to measure targeted hate in online comments, using a case study on Swedish politicians to evaluate its effectiveness and discuss potential improvements.

Contribution

It presents a simple, scalable approach for detecting targeted hate online and critically examines its limitations through a real-world case study.

Findings

The approach can identify hate speech directed at individuals.

It reveals shortcomings in dictionary-based detection methods.

Potential refinements are discussed for improved accuracy.

Abstract

Hateful comments, swearwords and sometimes even death threats are becoming a reality for many people today in online environments. This is especially true for journalists, politicians, artists, and other public figures. This paper describes how hate directed towards individuals can be measured in online environments using a simple dictionary-based approach. We present a case study on Swedish politicians, and use examples from this study to discuss shortcomings of the proposed dictionary-based approach. We also outline possibilities for potential refinements of the proposed approach.