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2020 SemEval SemEval 2020

XLP at SemEval-2020 Task 9: Cross-lingual Models with Focal Loss for Sentiment Analysis of Code-Mixing Language

Abstract

AbstractIn this paper, we present an approach for sentiment analysis in code-mixed language on twitter defined in SemEval-2020 Task 9. Our team (referred as LiangZhao) employ different multilingual models with weighted loss focused on complexity of code-mixing in sentence, in which the best model achieved f1-score of 0.806 and ranked 1st of subtask- Sentimix Spanglish. The performance of method is analyzed and each component of our architecture is demonstrated.

Authors

Yili Ma, Liang Zhao, Jie Hao

Topics

Natural Language Processing > Resources & Methods > Multilingual NLP Natural Language Processing > Applications > Sentiment Analysis

Keywords

sentiment analysis focal loss social media multilingual model cross-lingual model
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