Current State of Hinglish Text Sentiment Analysis

Abstract

The paper reviews about “sentiment analysis of Hinglish text”. Sentiment analysis is one of the important areas in the modern technical world. Research related to extracting sentiments, emotions from real world data comes under sentiment analysis, an extension of text mining. Sentiment analysis of text can be useful for various decision-making processes. However, social media comments do not follow strict grammatical rules, and they do a mixture of many languages, often written in non-original scripts. In India, lots of people use Hinglish (combination of Hindi and English) as their colloquial language in writings. Aspect based Sentiment analysis from Hinglish text is a challenging problem in the field of artificial intelligence. In this paper, the recent developments on sentiment analysis from English text as well as code mixed text and different problems related to the same have been presented. The main challenge of the Hinglish text model is the classification of aspect based sentiment .So to choose an appropriate classification model is vital. Different types of features of emotion text data and extraction techniques concerned with them are described in this paper along with the previous work review. The validity of various classification procedures was also analyzed. The analysis was also performed on text and textual properties of different ML techniques for real word analysis.