Correlation Analysis Between INR-USD Exchange Rates and Public Sentiments Using Twitter

Sentiment analysis is a tool to analyze textual data and categorize the emotional tone of the world's thought process regarding any subject of interest. ‘Twitter’ a social media app enables users to reverberate their opinions within the constraints of 280 characters, known as tweets. This study focuses on the examination of Twitter sentiments on the currency exchange rate between India and the USA using natural language processing techniques. The procedure involved extrication of tweets, data preprocessing, data tokenization, and then tweet polarization. Based on the polarity and sentiment score, the categorization of the sentiments results in either positive, negative, or neutral sentiment. The paper aims to understand the existence of correlation between the sentiments of twitter users and the change in the currency value of the respective country considering the parameters such as the frequency of tweets, their like count, and the time period. A model can be designed based on the relation based on the correlation hypothesis and can be used to predict the sentimental value on the postulated currency.