Sentiment Analysis of Social Media for Hindi Language

Abstract

In recent years, due to the availability of voluminous data on web for Indian languages, it has become an important task to analyze this data to retrieve useful information. Because of the growth of Indian language content, it is beneficial to utilize this explosion of data for the purpose of sentiment analysis. There are various applications of sentiment analysis in different domains such as recruitment, education, marketing, policy making, unemployment, fighting riots, terrorism, and education, etc. This research contributes to the development of Hindi sentiment analysis system for aspect, sentence and document level. The system is able to perform the sentiment analysis of Twitter posts. The system is available online at www.hindisenti.com. Hindi is the official language of India belonging to the family of Aryan languages. It is the 4th most spoken language with 310 million speakers across the world. In India, Hindi is spoken by a total of 422 million speakers; it s about 41% of total population of India. Therefore, there is a need to perform sentiment analysis in Hindi language so that the opinions of users in Hindi can be easily classified and proved useful for the users in decision making. Iin today s life, mostly people share their opinions on social media platforms. This motivated us to explore the field of sentiment analysis on social media for Hindi language. Although there are many differences in language structure of English and Hindi which arise different challenges while performing sentiment analysis on text dataset. This research work presents the description about the general process of sentiment analysis at different sentiment levels, i.e., aspect/feature, sentence and document level. This research depicts a systematic review in the field of sentiment analysis in general and Indian languages specifically. The current status of Indian languages in sentiment analysis is classified according to the Indian language families.