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A Novel Method to Gauge Audience Engagement with Televised Election Debates through Instant, Nuanced Feedback Elicitation

De Liddo, Anna; Plüss, Brian and Wilson, Paul (2017). A Novel Method to Gauge Audience Engagement with Televised Election Debates through Instant, Nuanced Feedback Elicitation. In: Communities and Technologies (C&T) 2017, 26-30 Jun 2017, Troyes, France, ACM.

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Despite a steep increase in the use of the Internet and handheld computing devices for media consumption, television is still of critical importance for democratic citizenship. Television continues to be the leading source of political information and its relevance has been recognised at policy level. In addition, television keeps evolving technologically and in how it is experienced by viewers. Nonetheless, the ways researchers have measured audience engagement with televised political events in real-time is often limited to small samples of viewers and is based upon a narrow range of responses.
In this paper we look at the audience of televised election debates, and propose a new method to gauge the richness and variety of citizens’ real-time responses at scale by capturing nuanced, non-intrusive, simple and measurable audience feedback. We report on a paper prototype experiment, in which we used a set of flashcards to test the method in an actual televised election debate scenario. We demonstrate how the method can improve our understanding of viewer responses to the debaters’ performances, to the contents in their arguments, and to the debate as media event. We conclude with design guidelines to implement the method on a mass scale in order to measure audience engagement with televised election debates in distributed contexts through audience feedback web and mobile applications.

Item Type: Conference or Workshop Item
Copyright Holders: 2017 ACM
Keywords: Televised election debates; audience research; audience feedback; collective intelligence; multimedia annotation; citizen engagement
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 49729
Depositing User: Anna De Liddo
Date Deposited: 28 Jun 2017 13:13
Last Modified: 28 May 2019 13:42
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