Real Time Tweet Summarization and Sentiment Analysis of Game Tournament

Streaming data analysis in real time is becoming the fastest and most efficient way to obtain useful knowledge from what is happening now, allowing organization to react quickly when problem appear or to detect new trends helping to improve their performance. There is substantial volume of tweet about each event, and there is press coverage of each event to serve as a gold standard. The problem we try to solve is that in absence of being live in front of television set, build data processing system that create informative data regarding tournament matches and correlate sentiment of fans to match play. Using twitter data, we find sub-events in game and sentiment of fans posting tweet related to game. We propose a system for real time summarization of scheduled sub-events for games using twitter data. We also propose an approach that analyzes feelings of people posting tweet. We focused on summarizing sporting events, specifically FIFA World Cup 2015 and IPL 2015. For a system using social media like twitter to keep track of things happening around, we look for following traits (I) Detection of bursty topic as soon as it emerges, (II) Summarization of related bursty topic, (III) Analyzing feelings of fans and correlating sentiment to game.