Measuring Voter's Candidate Preference Based on Affective Responses to Election Debates

In this paper we present the first analysis of facial responses to electoral debates measured automatically over the Internet. We show that significantly different responses can be detected from viewers with different political preferences and that similar expressions at significant moments can have...

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Bibliographic Details
Main Authors: McDuff, Daniel Jonathan (Contributor), El Kaliouby, Rana (Author), Kodra, Evan (Author), Picard, Rosalind W. (Contributor)
Other Authors: Massachusetts Institute of Technology. Media Laboratory (Contributor), Program in Media Arts and Sciences (Massachusetts Institute of Technology) (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2014-12-22T18:06:30Z.
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Online Access:Get fulltext
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100 1 0 |a McDuff, Daniel Jonathan  |e author 
100 1 0 |a Massachusetts Institute of Technology. Media Laboratory  |e contributor 
100 1 0 |a Program in Media Arts and Sciences   |q  (Massachusetts Institute of Technology)   |e contributor 
100 1 0 |a McDuff, Daniel Jonathan  |e contributor 
100 1 0 |a Picard, Rosalind W.  |e contributor 
700 1 0 |a El Kaliouby, Rana  |e author 
700 1 0 |a Kodra, Evan  |e author 
700 1 0 |a Picard, Rosalind W.  |e author 
245 0 0 |a Measuring Voter's Candidate Preference Based on Affective Responses to Election Debates 
260 |b Institute of Electrical and Electronics Engineers (IEEE),   |c 2014-12-22T18:06:30Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/92439 
520 |a In this paper we present the first analysis of facial responses to electoral debates measured automatically over the Internet. We show that significantly different responses can be detected from viewers with different political preferences and that similar expressions at significant moments can have very different meanings depending on the actions that appear subsequently. We used an Internet based framework to collect 611 naturalistic and spontaneous facial responses to five video clips from the 3rd presidential debate during the 2012 American presidential election campaign. Using this framework we were able to collect over 60% of these video responses (374 videos) within one day of the live debate and over 80% within three days. No participants were compensated for taking the survey. We present and evaluate a method for predicting independent voter preference based on automatically measured facial responses and self-reported preferences from the viewers. We predict voter preference with an average accuracy of over 73% (AUC 0.779). 
546 |a en_US 
655 7 |a Article 
773 |t Proceedings of the 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction