Have you ever wondered how to detect body-shaming, gender hate, and harassment in social media comments, especially in code-mixed languages written in Roman script? As an engineering student, I’m working on a self-initiated NLP project to tackle this issue.
My approach involves multi-class classification, using pretrained models like XLM-RoBERTa or IndicBERT, and handling spelling variations and mixed-language text. But I need guidance from someone experienced in NLP to review my approach and suggest resources.
If you’re interested in hate speech detection or NLP, I’d love to share my progress updates, datasets, and final results with you. Let’s collaborate and make a difference in the online community.
## The Importance of Hate Speech Detection
Hate speech detection is a crucial task in today’s digital age. With the rise of social media, online harassment and hate speech have become increasingly prevalent. It’s essential to develop effective methods to detect and mitigate hate speech, promoting a safer and more respectful online environment.
## The Challenges of Code-Mixed Roman Script Comments
Code-mixed Roman script comments pose a unique challenge in hate speech detection. The mixing of languages and scripts requires specialized models and techniques to accurately detect hate speech. This project aims to develop a robust approach to tackle this challenge.
## How You Can Help
If you’re an NLP expert or interested in hate speech detection, I’d appreciate your guidance and feedback on my project. Let’s work together to make a positive impact on the online community.