Year: 2024
Type: conference-paper
Abstract: Machine learning and deep learning models have shown great potential in detecting hate speech from social media posts.This study focuses on the homophobia and transphobia detection task of LT-EDI-2024 in English.Several machine learning models, a Deep Neural Network (DNN), and the Bidirectional Encoder Representations from Transformers (BERT) model have been trained on the provided dataset using different feature vectorization techniques.We secured top rank with the best macro-F1 score of 0.4963, which was achieved by fine-tuning the BERT model on the English test set.
Authors: Sargam Yadav, Abhishek Kaushik, Kevin McDaid
Institution: Dundalk Institute of Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Reduced inequalities
Open Access status: hybrid
OpenAlex ID: W7126378407