Offensive Language Detection on Twitter

TL;DR

This paper reviews offensive language detection on Twitter, combining existing methods with new ideas to improve accuracy, achieving 74% in classifying offensive tweets and discussing future challenges.

Contribution

It introduces novel ideas to enhance offensive language detection methods and reports a 74% accuracy on Twitter data.

Findings

Achieved 74% accuracy in offensive tweet classification

Identified key challenges in social media abusive content detection

Proposed improvements to existing detection approaches

Abstract

Detection of offensive language in social media is one of the key challenges for social media. Researchers have proposed many advanced methods to accomplish this task. In this report, we try to use the learnings from their approach and incorporate our ideas to improve upon them. We have successfully achieved an accuracy of 74% in classifying offensive tweets. We also list upcoming challenges in the abusive content detection in the social media world.