The exponential rise in social media users has revolutionized information accessibility and exchange. While these platforms serve various purposes, they also harbor negative elements, including hate speech and offensive behavior. Detecting hate speech in diverse languages has garnered significant attention in Natural Language Processing (NLP). This paper delves into hate speech detection in Tamil, particularly related to migration and refuge, contributing to the Caste/migration hate speech detection shared task. Employing a Convolutional Neural Network (CNN), our model achieved an F1 score of 0.76 in identifying hate speech and significant potential in the domain despite encountering complexities. We provide an overview of related research, methodology, and insights into the competition’s diverse performances, showcasing the landscape of hate speech detection nuances in the Tamil language.

Language Identification at the Word Level in Kannada-English Texts. This paper de- scribes the system paper of CoLI-Kanglish 2022 shared task. The goal of this task is to identify the different languages used in CoLI- Kanglish 2022. This dataset is distributed into different categories including Kannada, En- glish, Mixed-Language, Location, Name, and Others. This Code-Mix was compiled by CoLI- Kanglish 2022 organizers from posts on social media. We use two classification techniques, KNN and SVM, and achieve an F1-score of 0.58 and place third out of nine competitors.