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Articles

Googling for Trump: investigating online information seeking during the 2016 US presidential election

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Pages 1945-1955 | Received 07 Sep 2017, Accepted 03 May 2018, Published online: 11 May 2018
 

ABSTRACT

Search engines are increasingly used by citizens to seek out political information. Both the high frequency of use and the high credibility attributed to them by their users emphasize the need for research on search engines’ role in the democratic process. The present paper reports on a case study on online information seeking (OIS) via search engines during the 2016 US presidential election. Presidential candidate Donald Trump was largely unknown as a politician, was opposed by the vast majority in elite circles, broke the standard niceties of politics, and practiced a style of politics based on riot and conflict. Based on these attention-gaining maneuvers, we predicted that citizens would show an OIS bias toward Trump (compared to Hillary Clinton). Importantly, we hypothesized that key events broadly categorizable as gaffes, scandal, or gossip influenced OIS bias due to a general negativity bias. We used a retrospective database study relying on query share data from the search engine Google to test these assumptions. Consistent with our predictions, we found that there was a substantial OIS bias toward Trump and that negatively-valenced key events influenced the size of the OIS bias meaningfully. Of interest, additional analyses revealed a correlation between OIS bias and election outcome: The higher the OIS bias toward Trump, the less citizens voted for Trump. We offer post hoc theorizing on this explorative finding.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Florian Arendt is a postdoctoral researcher (“Akademischer Rat”) at the Department of Communication Science and Media Research, University of Munich (LMU) [email: [email protected]].

Nayla Fawzi is a postdoctoral researcher (“Akademischer Rat”) at the Department of Communication Science and Media Research, University of Munich (LMU) [email: [email protected]].

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