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Analyzing the public discourse on works of fiction - Detection and visualization of emotion in online coverage about HBO's Game of Thrones.
Scharl, Arno; Hubmann-Haidvogel, Alexander; Jones, Alistair; Fischl, Daniel; Kamolov, Ruslan; Weichselbraun, Albert; Rafelsberger, Walter.
  • Scharl A; Department of New Media Technology, MODUL University Vienna, Am Kahlenberg 1, 1190 Vienna, Austria; WebLyzard Technology, Puechlgasse 2/44, 1190 Vienna, Austria.
  • Hubmann-Haidvogel A; Department of New Media Technology, MODUL University Vienna, Am Kahlenberg 1, 1190 Vienna, Austria; WebLyzard Technology, Puechlgasse 2/44, 1190 Vienna, Austria.
  • Jones A; Department of New Media Technology, MODUL University Vienna, Am Kahlenberg 1, 1190 Vienna, Austria.
  • Fischl D; Department of New Media Technology, MODUL University Vienna, Am Kahlenberg 1, 1190 Vienna, Austria.
  • Kamolov R; Department of New Media Technology, MODUL University Vienna, Am Kahlenberg 1, 1190 Vienna, Austria.
  • Weichselbraun A; WebLyzard Technology, Puechlgasse 2/44, 1190 Vienna, Austria; University of Applied Sciences HTW Chur, Faculty of Information Sciences, Pulvermuehlestrasse 57, CH-7004, Chur, Switzerland.
  • Rafelsberger W; WebLyzard Technology, Puechlgasse 2/44, 1190 Vienna, Austria.
Inf Process Manag ; 52(1): 129-138, 2016 Jan.
Article en En | MEDLINE | ID: mdl-27065510
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 synchronized visual analytics components 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.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Año: 2016 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Año: 2016 Tipo del documento: Article