2021
EACL
EACL 2021
Autobots@LT-EDI-EACL2021: One World, One Family: Hope Speech Detection with BERT Transformer Model
Abstract
AbstractThe rapid rise of online social networks like YouTube, Facebook, Twitter allows people to express their views more widely online. However, at the same time, it can lead to an increase in conflict and hatred among consumers in the form of freedom of speech. Therefore, it is essential to take a positive strengthening method to research on encouraging, positive, helping, and supportive social media content. In this paper, we describe a Transformer-based BERT model for Hope speech detection for equality, diversity, and inclusion, submitted for LT-EDI-2021 Task 2. Our model achieves a weighted averaged f1-score of 0.93 on the test set.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio