Author:
Epstein Robert,Robertson Ronald E.
Abstract
Internet search rankings have a significant impact on consumer choices, mainly because users trust and choose higher-ranked results more than lower-ranked results. Given the apparent power of search rankings, we asked whether they could be manipulated to alter the preferences of undecided voters in democratic elections. Here we report the results of five relevant double-blind, randomized controlled experiments, using a total of 4,556 undecided voters representing diverse demographic characteristics of the voting populations of the United States and India. The fifth experiment is especially notable in that it was conducted with eligible voters throughout India in the midst of India’s 2014 Lok Sabha elections just before the final votes were cast. The results of these experiments demonstrate that (i) biased search rankings can shift the voting preferences of undecided voters by 20% or more, (ii) the shift can be much higher in some demographic groups, and (iii) search ranking bias can be masked so that people show no awareness of the manipulation. We call this type of influence, which might be applicable to a variety of attitudes and beliefs, the search engine manipulation effect. Given that many elections are won by small margins, our results suggest that a search engine company has the power to influence the results of a substantial number of elections with impunity. The impact of such manipulations would be especially large in countries dominated by a single search engine company.
Publisher
Proceedings of the National Academy of Sciences
Reference90 articles.
1. Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search;Joachims;Association for Computing Machinery Transactions on Information Systems,2007
2. In Google We Trust: Users’ Decisions on Rank, Position, and Relevance
3. Guan Z Cutrell E (2007) An eye tracking study of the effect of target rank on web search. Proceedings of the Special Interest Group for Computer-Human Interaction Conference on Human Factors in Computing Systems (ACM, New York), pp 417–420
4. Eye tracking and online search: Lessons learned and challenges ahead
5. Granka LA Joachim T Gay G (2004) Eye-tracking analysis of user behavior in www search. Proceedings of the 27th Annual International Association for Computing Machinery Special Interest Group on Information Retrieval Conference on Research and Development in Information Retrieval (ACM, New York, NY), pp 478–479
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