Characterization of Football Supporters from Twitter Conversations

Football (aka Soccer) is the most popular sport in the world. The popularity of the sport leads to several stories (some perhaps anecdotal) about supporters behaviors and to the emergence of rivalries such as the famous Barcelona-Real Madrid (in Spain). Little however has been done to characterize/profile online users' behaviors as football supporters and use them as an aggregate measure to club characterization. Today, the availability of data enable us to understand at a much greater scale if rivalries exist and if there are signatures that can be used to characterize supporting behavior. In this paper we use techniques from Data Science to characterize football supporters according to their activity on Twitter and to characterize clubs according to the behavior of their supporters. We show that it is possible to: (i) rank football clubs by their popularity and fans' dislike, (ii) identify the rivalries that exist between clubs and their supporters, and (iii) find specific signatures that repeat themselves across different clubs and in different countries. The results are evaluated on a large dataset of tweets relevant to major football leagues in Brazil and in the United Kingdom.