Developing a Multilingual Annotated Corpus of Misogyny and Aggression

TL;DR

This paper presents the creation of a multilingual annotated corpus of social media comments in Indian languages, focusing on misogyny and aggression, and reports baseline classification results.

Contribution

It introduces a new multilingual dataset with detailed annotations for misogyny and aggression in Indian social media comments, along with baseline classification experiments.

Findings

Over 20,000 comments annotated across three languages

Baseline classifiers achieved preliminary accuracy in detecting misogyny

Highlights challenges in annotating multilingual social media data

Abstract

In this paper, we discuss the development of a multilingual annotated corpus of misogyny and aggression in Indian English, Hindi, and Indian Bangla as part of a project on studying and automatically identifying misogyny and communalism on social media (the ComMA Project). The dataset is collected from comments on YouTube videos and currently contains a total of over 20,000 comments. The comments are annotated at two levels - aggression (overtly aggressive, covertly aggressive, and non-aggressive) and misogyny (gendered and non-gendered). We describe the process of data collection, the tagset used for annotation, and issues and challenges faced during the process of annotation. Finally, we discuss the results of the baseline experiments conducted to develop a classifier for misogyny in the three languages.