LT3 at SemEval-2020 Task 9: Cross-lingual Embeddings for Sentiment Analysis of Hinglish Social Media Text

Pranaydeep Singh, Els Lefever


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.
Anthology ID:
2020.semeval-1.173
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:
1288–1293
Language:
URL:
https://aclanthology.org/2020.semeval-1.173
DOI:
10.18653/v1/2020.semeval-1.173
Bibkey:
Cite (ACL):
Pranaydeep Singh and Els Lefever. 2020. LT3 at SemEval-2020 Task 9: Cross-lingual Embeddings for Sentiment Analysis of Hinglish Social Media Text. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1288–1293, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
LT3 at SemEval-2020 Task 9: Cross-lingual Embeddings for Sentiment Analysis of Hinglish Social Media Text (Singh & Lefever, SemEval 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.semeval-1.173.pdf