Analyzing the Public Discourse on Works of Fiction - Automatic Emotion Detection in Online Media Coverage about HBO's Game of Thrones

Citation

[scharl2015a, self.bib] Scharl, Arno, Hubmann-Haidvogel, Alexander, Jones, Alistair, Fischl, Daniel, Kamolov, Ruslan, Weichselbraun, Albert and Rafelsberger, Walter (2016). ''Analyzing the Public Discourse on Works of Fiction - Automatic Emotion Detection in Online Media Coverage about HBO's Game of Thrones'', Information Processing \& Management, pages 129--138, 52(1)

Abstract

This paper presents a Web intelligence portal that captures and aggregates news and social media coverage about “Game of Thrones”, an American drama television series created for the HBO television network based on George R. R. Martin's series of fantasy novels. The system collects content from the Web Sites of Anglo-American news media as well as from four social media platforms: Twitter, Facebook, Google+ and YouTube. An interactive dashboard with trend charts and complex map projections not only shows how often Game of Thrones events and characters are being mentioned by journalists and viewers, but also provides a real-time account of concepts that are being associated with the unfolding storyline and each new episode. Positive or negative sentiment is computed automatically, which sheds light on the perception of actors and new plot elements.

Keywords: Knowledge extraction, Web intelligence, Visual analytics, Interactive dashboard, Television series, Game of Thrones

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