Political ad portraits: a visual analysis of viewer reaction to online political spoof advertisements
The democratization of the Internet and the growing popularity of amateur video production have given rise to historic levels of voter engagement. In recent times, the populace has turned to YouTube and other similar websites to publicly voice their opinions through the posting of, and response to,...
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Published in | Journal of public affairs Vol. 10; no. 4; pp. 313 - 328 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Ltd
01.11.2010
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
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Summary: | The democratization of the Internet and the growing popularity of amateur video production have given rise to historic levels of voter engagement. In recent times, the populace has turned to YouTube and other similar websites to publicly voice their opinions through the posting of, and response to, amateur political videos. Political communication and campaign managers frequently struggle to consolidate, analyse, and respond to the vast array of commentary posted on the Internet in reply to these videos. The ability to quickly consolidate and interpret viewer responses to political videos provides campaign and communications' managers the opportunity to quickly make policy, positioning, or image changes. This is especially valuable considering that viewer responses provide a potentially unbiased picture of actual voter sentiment. Using the visualization software, Leximancer, we show how conversations around online political spoof videos can be mapped, interpreted, and used as a basis for strategic brand decision‐making. We discuss the implications of our findings, outline the technique's limitations, and trace avenues for further research.
Copyright © 2010 John Wiley & Sons, Ltd. |
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Bibliography: | istex:0B5BE37B9E1F85932A0B5FA46DA376238D6DCF32 ark:/67375/WNG-TZVQT117-K ArticleID:PA366 ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 1472-3891 1479-1854 |
DOI: | 10.1002/pa.366 |