Search engine manipulation effect: Difference between revisions

Revision as of 13:36, 5 November 2022

Revision as of 08:44, 30 November 2022

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{{notability|date=May 2022}}

{{Short description|Term}}

The '''search engine manipulation effect''' (SEME) is a term invented by [[Robert Epstein]] in 2015 to describe a hypothesized change in [[consumer behaviour|consumer preference]]s and [[voting behaviour|voting preferences]] by search engines. Rather than [[search engine optimization]] where advocates, websites, and businesses seek to optimize their placement in the search engine's algorithm, SEME focuses on the search engine companies themselves. According to the psychologist Epstein, search engine companies both could massively manipulate consumer and vote sentiment, and furthermore would do so to ensure their favored candidates win. Epstein propounded that such manipulations could shift the voting preferences of undecided voters by 20 percent or more, and up to 80 percent in some demographics, and would change the outcomes in over 25% of national elections.<ref>{{Cite journal|last1=Crain|first1=Matthew|last2=Nadler|first2=Anthony|date=2019|title=Political Manipulation and Internet Advertising Infrastructure|url=https://www.jstor.org/stable/10.5325/jinfopoli.9.2019.0370|journal=Journal of Information Policy|volume=9|pages=370–410|doi=10.5325/jinfopoli.9.2019.0370|jstor=10.5325/jinfopoli.9.2019.0370|s2cid=214217187|issn=2381-5892}}</ref><ref name=poli>{{Cite web|title = How Google Could Rig the 2016 Election|url = https://www.politico.com/magazine/story/2015/08/how-google-could-rig-the-2016-election-121548|access-date = 2015-08-24|first = Robert|last = Epstein |date=August 19, 2015 |publisher=Politico.com}}</ref><ref>{{Cite journal|last1=Epstein|first1=Robert|last2=Robertson|first2=Ronald E.|date=2015-08-18|title=The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections|journal=Proceedings of the National Academy of Sciences|language=en|volume=112|issue=33|pages=E4512–E4521|doi=10.1073/pnas.1419828112|issn=0027-8424|pmc=4547273|pmid=26243876|bibcode=2015PNAS..112E4512E|doi-access=free}}</ref>

In response to the allegations, [[Google]] denied re-ranking search results to manipulate user sentiment, or tweaking ranking specially for elections or political candidates.<ref>{{Cite web|url=https://www.politico.com/magazine/story/2015/08/google-2016-election-121766|title=A Flawed Elections Conspiracy Theory|website=POLITICO Magazine|access-date=2016-04-02}}</ref>

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In experiments conducted in the United States, the proportion of people who favored any candidate rose by between 37 and 63 percent after a single search session.<ref name=poli/>

Participants were randomly assigned to one of three groups in which search rankings favored either Candidate A, Candidate B or neither candidate. Participants were given brief descriptions of each candidate and then asked how much they liked and trusted each candidate and whom they would vote for. Then they were allowed up to 15 minutes to conduct online research on the candidates using a manipulated search engine.<ref>{{Cite journal |last=Epstein |first=Robert |last2=Robertson |first2=Ronald E. |date=2015-08-18 |title=The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections |url=https://www.primal.com.my/seo/what-is-ymyl-and-why-does-it-matter/ |journal=Proceedings of the National Academy of Sciences |language=en |volume= |issue= |doi= |issn= |pmc= |pmid=}}</ref> Each group had access to the same 30 search results—each linking to real web pages from a past election. Only the ordering of the results differed in the three groups. People could click freely on any result or shift between any of five different results pages.<ref name=poli/>

After searching, on all measures, opinions shifted in the direction of the candidate favored in the rankings. Trust, liking and voting preferences all shifted predictably.<ref>{{Cite web |url = https://suchmaschinen-optimierung-seo-google.de/suchmaschinenoptimierung/ |title = Suchmaschinenoptimierung |date = 6 October 2018 |language = de}}</ref> 36 percent of those who were unaware of the rankings bias shifted toward the highest ranked candidate, along with 45 percent of those who were aware of the bias.<ref name=poli/>

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=== United Kingdom ===

A UK experiment was conducted with nearly 4,000 people just before the 2015 national elections to examined ways to prevent manipulation. Randomizing the rankings or including alerts that identify bias had some suppressive effects.<ref name="poli" />

== 2016 U.S. presidential election ==