The Influence of Sentimental Analysis on Corporate Event Study

The main purpose of this study is to examine the influence of sentimental analysis of text mining data from social media sites on the cumulative abnormal returns of firms in the wake of a corporate event. Using market data for fifteen days around the announcement of the corporate event from the Bombay Stock Exchange, the study calculates the cumulative abnormal returns of firms. The cumulative abnormal returns are calculated using Event Study Market model. Text mining data were collected from twitter for fifteen days around the announcement of the event and were subjected to sentimental analysis in R-Studio which classifies the emotion and polarity of the tweets. With the help of Multiple Regression analysis the study examines the market reaction conveyed through sentiments of text mining data. The major finding of the study is that the text mining sentiments from social media strongly influence the cumulative abnormal returns of firms on a specific event. It is found that text sentiments have a high significant relation with the cumulative abnormal returns of firms which tells that it serve as an effective medium for the prediction of firm's abnormal returns. This study shows the importance of social media in the value creation of firms while taking huge investment/selling decisions, capturing of funds in the market, participation of interest in a company or on the wake of a particular event which may affect the firm and the industry in India thus leaving room for researchers in India for further study in this area. As social media is increasing in developing countries, this will be a constructive way to predict the market. So far, researchers have tested the causal relationship between a particular index performance (closing price of index) and text mining sentiments, while this study takes a different stand in the literature to analyze the influence of twitter sentiments over abnormal returns of firms. Thus this research is expected to add significant value to the literature of sentimental analysis.