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ExCode-Mixed: Explainable Approaches towards Sentiment Analysis on Code-Mixed Data using BERT models

Artificial Intelligence 2021-09-28 v2 Computation and Language Machine Learning

Abstract

The increasing use of social media sites in countries like India has given rise to large volumes of code-mixed data. Sentiment analysis of this data can provide integral insights into people's perspectives and opinions. Developing robust explainability techniques which explain why models make their predictions becomes essential. In this paper, we propose an adequate methodology to integrate explainable approaches into code-mixed sentiment analysis.

Keywords

Cite

@article{arxiv.2109.03200,
  title  = {ExCode-Mixed: Explainable Approaches towards Sentiment Analysis on Code-Mixed Data using BERT models},
  author = {Aman Priyanshu and Aleti Vardhan and Sudarshan Sivakumar and Supriti Vijay and Nipuna Chhabra},
  journal= {arXiv preprint arXiv:2109.03200},
  year   = {2021}
}

Comments

3 pages, 1 figure

R2 v1 2026-06-24T05:45:48.572Z