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Preparation of Rich Lists of Research Gaps in the Specific Sentiment Analysis Tasks of Code-mixed Indian Languages

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Abstract

Sentiment Analysis (SA) task for code-mixed Romanized text is an emerging area of research in Natural Language Processing (NLP). Since informal expression of sentiments in Romanized code-mixed Indian Languages (ILs) with emojis and/or emoticons is very common in social media, SA tasks for code-mixed posts/comments on ILs are being paid much attention by researchers. In the present survey, we have studied the evolution of language models over time, dataset details, research gaps, challenges towards building advanced models, possible recommendations to overcome those challenges, and determining the best-performing language models only for SA task on eight code-mixed ILs, namely Bengali–English, Hind–English, Kannada–English, Malayalam–English, Marathi–English, Punjabi–English, Telugu–English, and Tamil–English. Though many researchers have already explored the state-of-art text representation models for the SA task of resource-rich English language, contextual understanding and semantic feature extraction from non-standard code-mixed Romanized text of under-resourced ILs are yet to be explored to a large extent due to resource scarcity. We have focused on an exhaustive and comprehensive survey of very specific 70 research papers on SA tasks to list open research areas on code-mixed ILs. The present work will benefit researchers by providing a clear direction for future research scope in SA task in code-mixed IL pairs.

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  1. Symbiosis Institute of Computer Studies and Research, Symbiosis International (Deemed University), Pune, India

    Jatinderkumar R. Saini

  2. Faculty of Computational Science, Department of Computer Science, National Defence Academy, Pune, India

    Saikat Roy

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Saini, J.R., Roy, S. Preparation of Rich Lists of Research Gaps in the Specific Sentiment Analysis Tasks of Code-mixed Indian Languages. SN COMPUT. SCI. 5, 117 (2024). https://doi.org/10.1007/s42979-023-02408-6

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