LT3 at SemEval-2020 Task 9 : cross-lingual embeddings for sentiment analysis of Hinglish social media text
- Publication type
- C1
- Publication status
- Published
- Authors
- Singh, P.S, & Lefever, E.
- Series
- Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020)
- Pagination
- 1288-1293
- Publisher
- Association for Computational Linguistics (Barcelona, Spain)
- Conference
- the Fourteenth Workshop on Semantic Evaluation (SemEval 2020) (Barcelona, Spain)
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- (.pdf)
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Abstract
This paper describes our contribution to the SemEval-2020 Task 9 on Sentiment Analysis for
Code-mixed Social Media Text. We investigated two approaches to solve the task of Hinglish
sentiment analysis. The first approach uses cross-lingual embeddings resulting from projecting
Hinglish and pre-trained English FastText word embeddings in the same space. The second
approach incorporates pre-trained English embeddings that are incrementally retrained with a set
of Hinglish tweets. The results show that the second approach performs best, with an F1-score of
70.52% on the held-out test data.