conftrace_

2022 ACL ACL 2022

Sammaan@LT-EDI-ACL2022: Ensembled Transformers Against Homophobia and Transphobia

Abstract

AbstractHateful and offensive content on social media platforms can have negative effects on users and can make online communities more hostile towards certain people and hamper equality, diversity and inclusion. In this paper, we describe our approach to classify homophobia and transphobia in social media comments. We used an ensemble of transformer-based models to build our classifier. Our model ranked 2nd for English, 8th for Tamil and 10th for Tamil-English.

Authors

Ishan Sanjeev Upadhyay, Kv Aditya Srivatsa, Radhika Mamidi

Topics

Artificial Intelligence > Learning Paradigms > Transfer Learning Machine Learning > Core Methods > Classification

Keywords

ensemble learning text classification offensive language detection hate speech detection

More from ACL 2022

All ACL 2022 papers →

E8-IJS@LT-EDI-ACL2022 - BERT, AutoML and Knowledge-graph backed Detection of Depression

Nozza@LT-EDI-ACL2022: Ensemble Modeling for Homophobia and Transphobia Detection

KADO@LT-EDI-ACL2022: BERT-based Ensembles for Detecting Signs of Depression from Social Media Text

OPI@LT-EDI-ACL2022: Detecting Signs of Depression from Social Media Text using RoBERTa Pre-trained Language Models

FilipN@LT-EDI-ACL2022-Detecting signs of Depression from Social Media: Examining the use of summarization methods as data augmentation for text classification

NAYEL @LT-EDI-ACL2022: Homophobia/Transphobia Detection for Equality, Diversity, and Inclusion using SVM