On the generation of rich content metadata from social media

Abstract

This contribution proposes a framework to generate auxiliary rich TV content metadata by processing social networks data. Based on simple criteria to identify authoritative social media sources, we have analysed Twitter short messages relative to TV program content and devised a method to compute their informative value. We have extracted dozen of features and characterized such social data in terms of quality and relevancy. This is a first step towards integrating relevant social media information to enhance the description of TV content as well as for generating recommendations based on social data.