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
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
807–811
Language:
URL:
https://www.aclweb.org/anthology/S17-2136
DOI:
10.18653/v1/S17-2136
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S17-2136.pdf