Determining Event Outcomes: The Case of #fail

Srikala Murugan, Dhivya Chinnappa, Eduardo Blanco


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
Venues:
EMNLP | 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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2020.findings-emnlp.359.pdf
Optional supplementary material:
 2020.findings-emnlp.359.OptionalSupplementaryMaterial.txt