Review on Sentiment Analysis of Indian Languages with a Special Focus on Code Mixed Indian Languages

Given the wide applicability of social media platforms, individuals increasingly turn to the web to seek and share information, opinions, comments and suggestions which results in proliferation of user generated large volume of text data available for interpretation. A large number of users in India write their feelings or emotions in more than one language, thereby a large volume of text data is made available for Natural Language Processing (NLP) researchers. Sentiment Analysis (SA) of code-mixed text provides useful information in the field of politics, marketing, business, health, sports and what not. During the past decade the work on Sentiment Analysis of Indian language textual data, particularly in Hindi has got momentum in contrast to code-mixed Indian language text. However, due to non-availability of language and vocabulary (linguistic and lexical) tools and annotated resources, the task of Sentiment Analysis of Indian Languages becomes somehow difficult. In this study an attempt has been made to provide a detailed summary of Sentiment Analysis of Indian languages with a special focus on code mixed Indian Languages.