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

• URL: http://arxiv.org/abs/2010.11019v1
• Date: Wed, 21 Oct 2020 14:03:16 GMT
• Title: LT3 at SemEval-2020 Task 9: Cross-lingual Embeddings for Sentiment Analysis of Hinglish Social Media Text
• Authors: Pranaydeep Singh and Els Lefever
• Abstract summary: We investigate 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. The second approach incorporates pre-trained English embeddings that are incrementally retrained with a set of Hinglish tweets.
• Score: 1.0152838128195465
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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