Robert Epstein, Savannah Aries, Kelly Grebbien, Alyssa M. Salcedo, Vanessa R. Zankich
{"title":"The search suggestion effect (SSE): A quantification of how autocomplete search suggestions could be used to impact opinions and votes","authors":"Robert Epstein, Savannah Aries, Kelly Grebbien, Alyssa M. Salcedo, Vanessa R. Zankich","doi":"10.1016/j.chb.2024.108342","DOIUrl":null,"url":null,"abstract":"<div><p>News reports in 2016 suggested that a leading search engine was suppressing negative search suggestions for one US Presidential candidate but not for her opponent. We conducted a progressive series of five experiments to determine what effect differential suppression of this type might have on voters. We found that negative suggestions attract far more clicks than neutral or positive ones, consistent with extensive research on negativity bias, and that the differential suppression of negative search suggestions can turn a 50/50 split among undecided voters into more than a 90/10 split favoring the candidate for whom negative search suggestions were suppressed. We conclude that differentially suppressing negative search suggestions can have a dramatic impact on the opinions and voting preferences of undecided voters, potentially shifting a large number of votes without people knowing and without leaving a paper trail for authorities to trace.</p></div>","PeriodicalId":48471,"journal":{"name":"Computers in Human Behavior","volume":null,"pages":null},"PeriodicalIF":9.0000,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0747563224002103/pdfft?md5=542bfc9ec3db1ec0b448486029533245&pid=1-s2.0-S0747563224002103-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in Human Behavior","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0747563224002103","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
News reports in 2016 suggested that a leading search engine was suppressing negative search suggestions for one US Presidential candidate but not for her opponent. We conducted a progressive series of five experiments to determine what effect differential suppression of this type might have on voters. We found that negative suggestions attract far more clicks than neutral or positive ones, consistent with extensive research on negativity bias, and that the differential suppression of negative search suggestions can turn a 50/50 split among undecided voters into more than a 90/10 split favoring the candidate for whom negative search suggestions were suppressed. We conclude that differentially suppressing negative search suggestions can have a dramatic impact on the opinions and voting preferences of undecided voters, potentially shifting a large number of votes without people knowing and without leaving a paper trail for authorities to trace.
期刊介绍:
Computers in Human Behavior is a scholarly journal that explores the psychological aspects of computer use. It covers original theoretical works, research reports, literature reviews, and software and book reviews. The journal examines both the use of computers in psychology, psychiatry, and related fields, and the psychological impact of computer use on individuals, groups, and society. Articles discuss topics such as professional practice, training, research, human development, learning, cognition, personality, and social interactions. It focuses on human interactions with computers, considering the computer as a medium through which human behaviors are shaped and expressed. Professionals interested in the psychological aspects of computer use will find this journal valuable, even with limited knowledge of computers.