Impact of Tweets’ Sentiment Upon Stock Prices of Sport Companies: Can Fans Influence the Share Price of Their Preferred Sport Brand?

Abstract

This article aims to study the link between Twitter announces and stock prices of sport companies. Information extraction based on Natural Language Processing (NLP) allows to assess quickly and in a structured manner data from news, tweets, etc. Sentiment analysis provides an additional feature by categorizing the data in various classes (positive or negative sentiments, bullish or bearish market views etc...). In many instances, news, announces, social media content affects the evolution of stock prices. The research focuses on companies in the sport industry due to their popularity and the consistent number of followers on social networks, which provide a sound basis of analysis. The methodology encompasses the causality of tweets on stock price and the event study related to a significant event. The results analyze a sample of 18 listed companies in the sport industry.

Keywords: Sport Industry, Juventus, Lazio, Cristiano Ronaldo, NLP, Tweets, Sentiment Analysis, Granger Causality, Event Study

JEL Classification: G00