Exploratory Data Analysis on Code-mixed Misogynistic Comments

arXiv:2403.09709v1 Announce Type: new
Abstract: The problems of online hate speech and cyberbullying have significantly worsened since the increase in popularity of social media platforms such as YouTube and Twitter (X). Natural Language Processing (NLP) techniques have proven to provide a great advantage in automatic filtering such toxic content. Women are disproportionately more likely to be victims of online abuse. However, there appears to be a lack of studies that tackle misogyny detection in under-resourced languages. In this short paper, …

abstract analysis arxiv code cs.cl cyberbullying data data analysis exploratory filtering hate speech language language processing media mixed natural natural language natural language processing nlp platforms processing social social media social media platforms speech twitter type women youtube