  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.
