In my thesis I created an application consisting of several software components based on Python programming language, which I can use to make a real-time injury list of the English Premier League based on one of the most popular social networking website, Twitter. At the beginning, I examined Twitter data mining and Natural Language Processing related studies, then I got to know the basics of Python programming and Twitter services.
According to my excersise I downloaded and filtered the tweets through the Streaming API of the social networking website and stored them in a database. I used a MySQL relational database management system to keep a record of the entries, teams, players, injuries and injured players. I applied Natural Language Processing tools to analyse tweets offline at first, then in real-time. I saved the results in an HTML table and compared it to a website dealing with sports injuries.
With the help of this application we can get information faster than official news without any manual intervention, capitalizing on the benefits of social media. It might mean an advantage in sports betting for instance, although the applied methods can be utilized in different aspects.