Improving Human Needs Categorization of Events with Semantic Classification

Haibo Ding, Ellen Riloff, Zhe Feng


Abstract
Human Needs categories have been used to characterize the reason why an affective event is positive or negative. For example, “I got the flu” and “I got fired” are both negative (undesirable) events, but getting the flu is a Health problem while getting fired is a Financial problem. Previous work created learning models to assign events to Human Needs categories based on their words and contexts. In this paper, we introduce an intermediate step that assigns words to relevant semantic concepts. We create lightly supervised models that learn to label words with respect to 10 semantic concepts associated with Human Needs categories, and incorporate these labels as features for event categorization. Our results show that recognizing relevant semantic concepts improves both the recall and precision of Human Needs categorization for events.
Anthology ID:
S19-1022
Volume:
Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Venues:
SemEval | *SEM
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
198–204
Language:
URL:
https://aclanthology.org/S19-1022
DOI:
10.18653/v1/S19-1022
Bibkey:
Cite (ACL):
Haibo Ding, Ellen Riloff, and Zhe Feng. 2019. Improving Human Needs Categorization of Events with Semantic Classification. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 198–204, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
Improving Human Needs Categorization of Events with Semantic Classification (Ding et al., SemEval-*SEM 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/S19-1022.pdf