UCSC-NLP at SemEval-2017 Task 4: Sense n-grams for Sentiment Analysis in Twitter
José Abreu, Iván Castro, Claudia Martínez, Sebastián Oliva, Yoan Gutiérrez
Abstract
This paper describes the system submitted to SemEval-2017 Task 4-A Sentiment Analysis in Twitter developed by the UCSC-NLP team. We studied how relationships between sense n-grams and sentiment polarities can contribute to this task, i.e. co-occurrences of WordNet senses in the tweet, and the polarity. Furthermore, we evaluated the effect of discarding a large set of features based on char-grams reported in preceding works. Based on these elements, we developed a SVM system, which exploring SentiWordNet as a polarity lexicon. It achieves an F1=0.624of average. Among 39 submissions to this task, we ranked 10th.- Anthology ID:
- S17-2136
- Volume:
- Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Steven Bethard, Marine Carpuat, Marianna Apidianaki, Saif M. Mohammad, Daniel Cer, David Jurgens
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 807–811
- Language:
- URL:
- https://aclanthology.org/S17-2136
- DOI:
- 10.18653/v1/S17-2136
- Cite (ACL):
- José Abreu, Iván Castro, Claudia Martínez, Sebastián Oliva, and Yoan Gutiérrez. 2017. UCSC-NLP at SemEval-2017 Task 4: Sense n-grams for Sentiment Analysis in Twitter. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 807–811, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- UCSC-NLP at SemEval-2017 Task 4: Sense n-grams for Sentiment Analysis in Twitter (Abreu et al., SemEval 2017)
- PDF:
- https://preview.aclanthology.org/fix-volume-bibkeys/S17-2136.pdf