Generating Objective Summaries of Sports Matches Using Social Media

Abstract

Social media has become a platform where users post their messages about a wide range of topics, making it a useful source of information to summarize events such as sports matches. Previous summaries of sports matches generated using social media tended to be biased towards one of the teams, due to a high proportion of the posts used being from fans of the teams involved. This is problematic because in general people desire summaries that are free from bias and objective. To remedy this problem and generate higher quality summaries, we propose two approaches. The first is a function maximization method which measures the objectivity of each post based on its constituent words. The second is a neural network-based approach, where we use an encoder-decoder architecture. Then, we compare them with an existing approach and show promising results that indicate the effectiveness of our methods.CCS CONCEPTS • Information systems → Social networks; • Computing methodologies → Natural language generation; Information extraction.