Offensive Language Detection on Twitter
arXiv:2209.14091v11 citationsh-index: 2
Originality Synthesis-oriented
AI Analysis
This work addresses the challenge of abusive content detection for social media platforms, but it is incremental in nature.
The paper tackled the problem of detecting offensive language on Twitter by building on existing methods, achieving an accuracy of 74% in classifying offensive tweets.
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.