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The Matter of Chance: Auditing Web Search Results Related to the 2020 U.S. Presidential Primary Elections Across Six Search Engines
[journal article]
Abstract We examine how six search engines filter and rank information in relation to the queries on the U.S. 2020 presidential primary elections under the default - that is nonpersonalized - conditions. For that, we utilize an algorithmic auditing methodology that uses virtual agents to conduct large-scale ... view more
We examine how six search engines filter and rank information in relation to the queries on the U.S. 2020 presidential primary elections under the default - that is nonpersonalized - conditions. For that, we utilize an algorithmic auditing methodology that uses virtual agents to conduct large-scale analysis of algorithmic information curation in a controlled environment. Specifically, we look at the text search results for "us elections," "donald trump," "joe biden," "bernie sanders" queries on Google, Baidu, Bing, DuckDuckGo, Yahoo, and Yandex, during the 2020 primaries. Our findings indicate substantial differences in the search results between search engines and multiple discrepancies within the results generated for different agents using the same search engine. It highlights that whether users see certain information is decided by chance due to the inherent randomization of search results. We also find that some search engines prioritize different categories of information sources with respect to specific candidates. These observations demonstrate that algorithmic curation of political information can create information inequalities between the search engine users even under nonpersonalized conditions. Such inequalities are particularly troubling considering that search results are highly trusted by the public and can shift the opinions of undecided voters as demonstrated by previous research.... view less
Keywords
search engine; Internet; information-seeking behavior; presidential election; United States of America; algorithm; source of information
Classification
Interactive, electronic Media
Free Keywords
web search elections; U.S. elections; algorithmic auditing
Document language
English
Publication Year
2021
Page/Pages
p. 1-17
Journal
Social Science Computer Review (2021) OnlineFirst
DOI
https://doi.org/10.1177/08944393211006863
ISSN
1552-8286
Status
Postprint; peer reviewed
Licence
Creative Commons - Attribution-Noncommercial-No Derivative Works 4.0