Abstract
This paper targets the task of determining event outcomes in social media. We work with tweets containing either #cookingFail or #bakingFail, and show that many of the events described in them resulted in something edible. Tweets that contain images are more likely to result in edible albeit imperfect outcomes. Experimental results show that edibility is easier to predict than outcome quality.- Anthology ID:
- 2020.findings-emnlp.359
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2020
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Trevor Cohn, Yulan He, Yang Liu
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4021–4033
- Language:
- URL:
- https://aclanthology.org/2020.findings-emnlp.359
- DOI:
- 10.18653/v1/2020.findings-emnlp.359
- Cite (ACL):
- Srikala Murugan, Dhivya Chinnappa, and Eduardo Blanco. 2020. Determining Event Outcomes: The Case of #fail. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4021–4033, Online. Association for Computational Linguistics.
- Cite (Informal):
- Determining Event Outcomes: The Case of #fail (Murugan et al., Findings 2020)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2020.findings-emnlp.359.pdf