Abstract
Emotion is fundamental to humanity. The ability to perceive, understand and respond to social interactions in a human-like manner is one of the most desired capabilities in artificial agents, particularly in social-media bots. Over the past few years, computational understanding and detection of emotional aspects in language have been vital in advancing human-computer interaction. The WASSA Shared Task 2021 released a dataset of news-stories across two tracks, Track-1 for Empathy and Distress Prediction and Track-2 for Multi-Dimension Emotion prediction at the essay-level. We describe our system entry for the WASSA 2021 Shared Task (for both Track-1 and Track-2), where we leveraged the information from Pre-trained language models for Track-specific Tasks. Our proposed models achieved an Average Pearson Score of 0.417, and a Macro-F1 Score of 0.502 in Track 1 and Track 2, respectively. In the Shared Task leaderboard, we secured the fourth rank in Track 1 and the second rank in Track 2.- Anthology ID:
- 2021.wassa-1.30
- Volume:
- Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
- Month:
- April
- Year:
- 2021
- Address:
- Online
- Editors:
- Orphee De Clercq, Alexandra Balahur, Joao Sedoc, Valentin Barriere, Shabnam Tafreshi, Sven Buechel, Veronique Hoste
- Venue:
- WASSA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 274–280
- Language:
- URL:
- https://aclanthology.org/2021.wassa-1.30
- DOI:
- Cite (ACL):
- Yash Butala, Kanishk Singh, Adarsh Kumar, and Shrey Shrivastava. 2021. Team Phoenix at WASSA 2021: Emotion Analysis on News Stories with Pre-Trained Language Models. In Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 274–280, Online. Association for Computational Linguistics.
- Cite (Informal):
- Team Phoenix at WASSA 2021: Emotion Analysis on News Stories with Pre-Trained Language Models (Butala et al., WASSA 2021)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2021.wassa-1.30.pdf
- Code
- yashbutala/WASSA
- Data
- CARER