TY - GEN
T1 - Determining event outcomes
T2 - Findings of the Association for Computational Linguistics, ACL 2020: EMNLP 2020
AU - Murugan, Srikala
AU - Chinnappa, Dhivya
AU - Blanco, Eduardo
N1 - Funding Information:
This material is based in part upon work supported by the National Science Foundation under Grant No. 1820666. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.
Publisher Copyright:
© 2020 Association for Computational Linguistics
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85118466869&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85118466869&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85118466869
T3 - Findings of the Association for Computational Linguistics Findings of ACL: EMNLP 2020
SP - 4021
EP - 4033
BT - Findings of the Association for Computational Linguistics Findings of ACL
PB - Association for Computational Linguistics (ACL)
Y2 - 16 November 2020 through 20 November 2020
ER -