Two Sides to Every Story: Subjective Event Summarization of Sports Events using Twitter.

Abstract

Ask two people to describe an event they have both experienced, and you will usually hear two very different accounts. Witnesses bring their own preconceptions and biases which makes objective story-telling all but impossi-ble. Despite this, recent work on algorithmic topic detection, event summarization and con-tent generation often has a stated aim of ob-jectively answering the question, “What just happened? ” Here, in contrast, we ask “How did people respond to what just happened?” We describe some initial studies of sports fans’ discussions of football matches through online social networks. During major sporting events, spectators send many messages through social networks like Twitter. These messages can be analysed to detect events, such as goals, and to provide summaries of sports events. Our aim is to pro-duce a subjective summary of events as seen by the fans. We describe simple rules to esti-mate which team each tweeter supports and so divide the tweets between the two teams. We then use a topic detection algorithm to dis-cover the main topics discussed by each set of fans. Finally we compare these to live main-stream media reports of the event and select Copyright c © by the paper’s authors. Copying permitted only for private and academic purposes.