Abstract
The “Sentiment Analysis for Code-Mixed Social Media Text” task at the SemEval 2020 competition focuses on sentiment analysis in code-mixed social media text , specifically, on the combination of English with Spanish (Spanglish) and Hindi (Hinglish). In this paper, we present a system able to classify tweets, from Spanish and English languages, into positive, negative and neutral. Firstly, we built a classifier able to provide corresponding sentiment labels. Besides the sentiment labels, we provide the language labels at the word level. Secondly, we generate a word-level representation, using Convolutional Neural Network (CNN) architecture. Our solution indicates promising results for the Sentimix Spanglish-English task (0.744), the team, Lavinia_Ap, occupied the 9th place. However, for the Sentimix Hindi-English task (0.324) the results have to be improved.- Anthology ID:
- 2020.semeval-1.118
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Editors:
- Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 928–933
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.118
- DOI:
- 10.18653/v1/2020.semeval-1.118
- Cite (ACL):
- Lavinia Aparaschivei, Andrei Palihovici, and Daniela Gîfu. 2020. FII-UAIC at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using CNN. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 928–933, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- FII-UAIC at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using CNN (Aparaschivei et al., SemEval 2020)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2020.semeval-1.118.pdf
- Data
- SentiMix