Abstract
In this paper we examine existing sentiment lexicons and sense-based sentiment-tagged corpora to find out how sense and concept-based semantic relations effect sentiment scores (for polarity and valence). We show that some relations are good predictors of sentiment of related words: antonyms have similar valence and opposite polarity, synonyms similar valence and polarity, as do many derivational relations. We use this knowledge and existing resources to build a sentiment annotated wordnet of English, and show how it can be used to produce sentiment lexicons for other languages using the Open Multilingual Wordnet.- Anthology ID:
- 2022.lrec-1.7
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 61–69
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.7
- DOI:
- Cite (ACL):
- Francis Bond and Merrick Choo. 2022. Sense and Sentiment. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 61–69, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Sense and Sentiment (Bond & Choo, LREC 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/2022.lrec-1.7.pdf
- Code
- bond-lab/sensitive + additional community code