LIPN-UAM at EmoInt-2017:Combination of Lexicon-based features and Sentence-level Vector Representations for Emotion Intensity Determination

Davide Buscaldi, Belem Priego


Abstract
This paper presents the combined LIPN-UAM participation in the WASSA 2017 Shared Task on Emotion Intensity. In particular, the paper provides some highlights on the Tweetaneuse system that was presented to the shared task. We combined lexicon-based features with sentence-level vector representations to implement a random forest regressor.
Anthology ID:
W17-5236
Volume:
Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Alexandra Balahur, Saif M. Mohammad, Erik van der Goot
Venue:
WASSA
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
255–258
Language:
URL:
https://aclanthology.org/W17-5236
DOI:
10.18653/v1/W17-5236
Bibkey:
Cite (ACL):
Davide Buscaldi and Belem Priego. 2017. LIPN-UAM at EmoInt-2017:Combination of Lexicon-based features and Sentence-level Vector Representations for Emotion Intensity Determination. In Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 255–258, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
LIPN-UAM at EmoInt-2017:Combination of Lexicon-based features and Sentence-level Vector Representations for Emotion Intensity Determination (Buscaldi & Priego, WASSA 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-5236.pdf