Machine Learning Techniques for Sentiment Analysis of Code-Mixed and Switched Indian Social Media Text Corpus - A Comprehensive Review

A comprehensive review of sentiment analysis for code-mixed and switched text corpus Indian social media using machine learning (ML) approaches, based on recent research studies has been presented in this paper. Code-mixing switching are linguistic behavior shown by the bilingual/multilingual population, primarily spoken but also written communication, especially media. involves combining lower units like words phrases a language into sentences other (the base language) code-switching to another language, length one sentence or more. In code-mixing switching, bilingual person takes more from introduces them while communicating that mode. People nowadays express their views opinions several issues multilingual countries, people English as well native languages. Several reasons can be attributed code-mixing. Lack knowledge particular subject, being empathetic, interjection clarification some name. Sentiment monolingual content carried out last two decades. However, during years, Natural Language Processing (NLP) focus shifted towards exploration data, thereby, making code mixed an evolving field research. Systems have developed ML techniques predict polarity fine tune existing models improve performance.