Abstract
The 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.- Anthology ID:
- 2021.ltedi-1.21
- Volume:
- Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion
- Month:
- April
- Year:
- 2021
- Address:
- Kyiv
- Editors:
- Bharathi Raja Chakravarthi, John P. McCrae, Manel Zarrouk, Kalika Bali, Paul Buitelaar
- Venue:
- LTEDI
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 143–148
- Language:
- URL:
- https://aclanthology.org/2021.ltedi-1.21
- DOI:
- Cite (ACL):
- Sunil Gundapu and Radhika Mamidi. 2021. Autobots@LT-EDI-EACL2021: One World, One Family: Hope Speech Detection with BERT Transformer Model. In Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion, pages 143–148, Kyiv. Association for Computational Linguistics.
- Cite (Informal):
- Autobots@LT-EDI-EACL2021: One World, One Family: Hope Speech Detection with BERT Transformer Model (Gundapu & Mamidi, LTEDI 2021)
- PDF:
- https://preview.aclanthology.org/ml4al-ingestion/2021.ltedi-1.21.pdf
- Data
- HopeEDI