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
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W17-5236.pdf