Filippo Trevisan
The Google voter: search engines and electoral information flows in the new media ecology
Trevisan, Filippo; Hoskins, Andrew; Oates, Sarah; Mahlouly, Dounia
Authors
Andrew Hoskins
Sarah Oates
DR Dounia Mahlouly dm56@soas.ac.uk
Lecturer in Global Media & Communication
Abstract
This paper explores key Internet search trends for electoral information vis-à-vis the broader media ecology in the UK and the US. An innovative methodology is introduced that maps the informational trajectories of key election events by combining Google Trends data linked to significant news events during the campaigns. While the research found spikes of search that suggested a seemingly trivial event in the US could drive voters to search out deeper information on related policy issues, the study did not find the same phenomenon in the UK. This invites a reflection on the opportunities available to Internet users/voters in the changing informational landscape and how scholars can leverage Google Trends records to better understand how voters seek information in new and evolving media ecologies.
Citation
Trevisan, F., Hoskins, A., Oates, S., & Mahlouly, D. (2018). The Google voter: search engines and electoral information flows in the new media ecology. Information, Communication and Society, 21(1), 111-128. https://doi.org/10.1080/1369118X.2016.1261171
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 11, 2016 |
Online Publication Date | Dec 1, 2016 |
Publication Date | Jan 1, 2018 |
Deposit Date | Jun 3, 2019 |
Publicly Available Date | Jun 3, 2019 |
Journal | Information, Communication and Society |
Print ISSN | 1369-118X |
Electronic ISSN | 1468-4462 |
Publisher | Taylor and Francis Group |
Peer Reviewed | Peer Reviewed |
Volume | 21 |
Issue | 1 |
Pages | 111-128 |
DOI | https://doi.org/10.1080/1369118X.2016.1261171 |
Keywords | Google Trends, elections, Internet search, media ecology, UK, US |
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Copyright Statement
© 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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