CMSAOne@Dravidian-CodeMix-FIRE2020: A Meta Embedding and Transformer model for Code-Mixed Sentiment Analysis on Social Media Text

• URL: http://arxiv.org/abs/2101.09004v1
• Date: Fri, 22 Jan 2021 08:48:27 GMT
• Title: CMSAOne@Dravidian-CodeMix-FIRE2020: A Meta Embedding and Transformer model for Code-Mixed Sentiment Analysis on Social Media Text
• Authors: Suman Dowlagar, Radhika Mamidi
• Abstract summary: Code-mixing (CM) is a frequently observed phenomenon that uses multiple languages in an utterance or sentence. Sentiment analysis (SA) is a fundamental step in NLP and is well studied in the monolingual text. This paper proposes a meta embedding with a transformer method for sentiment analysis on the Dravidian code-mixed dataset.
• Score: 9.23545668304066
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Code-mixing(CM) is a frequently observed phenomenon that uses multiple languages in an utterance or sentence. CM is mostly practiced on various social media platforms and in informal conversations. Sentiment analysis (SA) is a fundamental step in NLP and is well studied in the monolingual text. Code-mixing adds a challenge to sentiment analysis due to its non-standard representations. This paper proposes a meta embedding with a transformer method for sentiment analysis on the Dravidian code-mixed dataset. In our method, we used meta embeddings to capture rich text representations. We used the proposed method for the Task: "Sentiment Analysis for Dravidian Languages in Code-Mixed Text", and it achieved an F1 score of $0.58$ and $0.66$ for the given Dravidian code mixed data sets. The code is provided in the Github https://github.com/suman101112/fire-2020-Dravidian-CodeMix.

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