Tracking and analyzing TV content on the web through social and ontological knowledge

People on the Web talk about television. TV users' social activities implicitly connect the concepts referred to by videos, news, comments, and posts. The strength of such connections may change as the perception of users on the Web changes over time. With the goal of leveraging users' social activities to better understand how TV programs are perceived by the TV public and how the users' interests evolve in time, we introduce a knowledge graph to model the integration of the heterogeneous and dynamic data coming from different information sources, including broadcasters' archives, online newspapers, blogs, web encyclopedias, social media platforms, and social networks, which play a role in what we call the "extended life" of TV content. We show how our graph model captures multiple aspects of the television domain, from the semantic characterization of the TV content, to the temporal evolution of its social characterization and of its social perception. Through a real use-case analysis, based on the instance of our knowledge graph extracted from (the analysis of) a set of episodes of an Italian TV talk show, we discuss the involvement of the public of the considered program.