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Auditing the Personalization and Composition of Politically-Related Search Engine Results Pages

Authors:

Ronald E. Robertson,

Christo WilsonAuthors Info & Claims

WWW '18: Proceedings of the 2018 World Wide Web Conference

Pages 955 - 965

https://doi.org/10.1145/3178876.3186143

Published: 23 April 2018 Publication History

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Abstract

Search engines are a primary means through which people obtain information in today»s connected world. Yet, apart from the search engine companies themselves, little is known about how their algorithms filter, rank, and present the web to users. This question is especially pertinent with respect to political queries, given growing concerns about filter bubbles, and the recent finding that bias or favoritism in search rankings can influence voting behavior. In this study, we conduct a targeted algorithm audit of Google Search using a dynamic set of political queries. We designed a Chrome extension to survey participants and collect the Search Engine Results Pages (SERPs) and autocomplete suggestions that they would have been exposed to while searching our set of political queries during the month after Donald Trump»s Presidential inauguration. Using this data, we found significant differences in the composition and personalization of politically-related SERPs by query type, subjects» characteristics, and date.

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Cited By

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cover image ACM Other conferences

WWW '18: Proceedings of the 2018 World Wide Web Conference

April 2018

2000 pages

ISBN:9781450356398

General Chairs:
Pierre-Antoine Champin
Universitè Claude Bernard Lyon 1, France
,
Fabien Gandon
Inria, Université Côte d'Azur, CNRS, I3S, France
,
Lionel Médini
Université Claude Bernard Lyon 1, France
,
Program Chairs:
Mounia Lalmas
Spotify, UK
,
Panagiotis G. Ipeirotis
New York University, USA

Copyright © 2018 ACM.

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

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Published: 23 April 2018

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WWW '18

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WWW '18: The Web Conference 2018

April 23 - 27, 2018

Lyon, France

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WWW '18 Paper Acceptance Rate 170 of 1,155 submissions, 15%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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Perreault BLee JShava RMustafaraj E(2024)Algorithmic Misjudgement in Google Search Results: Evidence from Auditing the US Online Electoral Information EnvironmentProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658916(433-443)Online publication date: 3-Jun-2024
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