Sentiment Analysis on Multiple Indian Languages (International Journal of Food and Nutritional Sciences, 2022)
Sentiment analysis has become popular in the computer science community as it isessential for moderating and analyzing information across the internet. There are variousapplications for sentiment analysis, such as opinion mining, social media monitoring, andmarket research. Sentiment analysis in Indian languages is gaining importance due to thegrowth of content on social media, news articles, and other online platforms in Indianlanguages. Since India is a diversified country it has many languages that are used bymillions of people but many Indian languages do not have enough resources for moderationon the internet to analyze the sentiment in the text to use them for either eradicating hatespeech or to improve the productivity of companies by the understanding of customer needsfrom reviews. This paper explains an approach that helps in analyzing the sentiment whichhelps in content moderation and avoiding negativity on the internet. This approach uses theBERT algorithm for sentiment analysis in English. All the text in other languages will betranslated into English and their sentiment is then analyzed. In this approach, we use theBERT algorithm for sentiment analysis on translated English text. This approach workswell because sentiment analysis using BERT gives higher accuracy and the translation oftext from Indian languages is made easy by the advent of natural language processing. Bycombining both the above-discussed processes we can analyze the sentiment in multipleIndian languages.