A Datamining Approach for Emotions Extraction and Discovering Cricketers performance from Stadium to Sensex

TL;DR

This paper presents a data mining approach to analyze social media emotions related to cricket players and correlates these emotions with stock market performance of associated brands, revealing a connection between player performance, fan emotions, and stock behavior.

Contribution

It introduces a novel method for extracting emotions from tweets during cricket events and links these emotions to stock market trends of brands endorsing or sponsoring players.

Findings

Fan emotions correlate with player performance.

Stock market behavior of brands is influenced by player performance.

Social media sentiment reflects real-world economic impacts.

Abstract

Microblogging sites are the direct platform for the users to express their views. It has been observed from previous studies that people are viable to flaunt their emotions for events (eg. natural catastrophes, sports, academics etc.), for persons (actor/actress, sports person, scientist) and for the places they visit. In this study we focused on a sport event, particularly the cricket tournament and collected the emotions of the fans for their favorite players using their tweets. Further, we acquired the stock market performance of the brands which are either endorsing the players or sponsoring the match in the tournament. It has been observed that performance of the player triggers the users to flourish their emotions over social media therefore, we observed correlation between players performance and fans' emotions. Therefore, we found the direct connection between player's performance with brand's behavior on stock market.