Measuring political personalization of Google news search

Huyen Le, Andrew High, Raven Maragh, Timothy Havens, Brian Ekdale, Zubair Shafiq

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There is a growing concern about the extent to which algorithmic personalization limits people's exposure to diverse viewpoints, thereby creating “filter bubbles" or “echo chambers." Prior research on web search personalization has mainly reported location-based personalization of search results. In this paper, we investigate whether web search results are personalized based on a user's browsing history, which can be inferred by search engines via third-party tracking. Specifically, we develop a “sock puppet" auditing system in which a pair of fresh browser profiles, first, visits web pages that reflect divergent political discourses and, second, executes identical politically oriented Google News searches. Comparing the search results returned by Google News for distinctly trained browser profiles, we observe statistically significant personalization that tends to reinforce the presumed partisanship.

Original languageEnglish (US)
Title of host publicationThe Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019
PublisherAssociation for Computing Machinery, Inc
Pages2957-2963
Number of pages7
ISBN (Electronic)9781450366748
DOIs
StatePublished - May 13 2019
Event2019 World Wide Web Conference, WWW 2019 - San Francisco, United States
Duration: May 13 2019May 17 2019

Publication series

NameThe Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019

Conference

Conference2019 World Wide Web Conference, WWW 2019
CountryUnited States
CitySan Francisco
Period5/13/195/17/19

Fingerprint

Search engines
Websites

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

Cite this

Le, H., High, A., Maragh, R., Havens, T., Ekdale, B., & Shafiq, Z. (2019). Measuring political personalization of Google news search. In The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019 (pp. 2957-2963). (The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019). Association for Computing Machinery, Inc. https://doi.org/10.1145/3308558.3312504
Le, Huyen ; High, Andrew ; Maragh, Raven ; Havens, Timothy ; Ekdale, Brian ; Shafiq, Zubair. / Measuring political personalization of Google news search. The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019. Association for Computing Machinery, Inc, 2019. pp. 2957-2963 (The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019).
@inproceedings{94e5552624ef4148951664d922b6f67b,
title = "Measuring political personalization of Google news search",
abstract = "There is a growing concern about the extent to which algorithmic personalization limits people's exposure to diverse viewpoints, thereby creating “filter bubbles{"} or “echo chambers.{"} Prior research on web search personalization has mainly reported location-based personalization of search results. In this paper, we investigate whether web search results are personalized based on a user's browsing history, which can be inferred by search engines via third-party tracking. Specifically, we develop a “sock puppet{"} auditing system in which a pair of fresh browser profiles, first, visits web pages that reflect divergent political discourses and, second, executes identical politically oriented Google News searches. Comparing the search results returned by Google News for distinctly trained browser profiles, we observe statistically significant personalization that tends to reinforce the presumed partisanship.",
author = "Huyen Le and Andrew High and Raven Maragh and Timothy Havens and Brian Ekdale and Zubair Shafiq",
year = "2019",
month = "5",
day = "13",
doi = "10.1145/3308558.3312504",
language = "English (US)",
series = "The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019",
publisher = "Association for Computing Machinery, Inc",
pages = "2957--2963",
booktitle = "The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019",

}

Le, H, High, A, Maragh, R, Havens, T, Ekdale, B & Shafiq, Z 2019, Measuring political personalization of Google news search. in The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019. The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019, Association for Computing Machinery, Inc, pp. 2957-2963, 2019 World Wide Web Conference, WWW 2019, San Francisco, United States, 5/13/19. https://doi.org/10.1145/3308558.3312504

Measuring political personalization of Google news search. / Le, Huyen; High, Andrew; Maragh, Raven; Havens, Timothy; Ekdale, Brian; Shafiq, Zubair.

The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019. Association for Computing Machinery, Inc, 2019. p. 2957-2963 (The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Measuring political personalization of Google news search

AU - Le, Huyen

AU - High, Andrew

AU - Maragh, Raven

AU - Havens, Timothy

AU - Ekdale, Brian

AU - Shafiq, Zubair

PY - 2019/5/13

Y1 - 2019/5/13

N2 - There is a growing concern about the extent to which algorithmic personalization limits people's exposure to diverse viewpoints, thereby creating “filter bubbles" or “echo chambers." Prior research on web search personalization has mainly reported location-based personalization of search results. In this paper, we investigate whether web search results are personalized based on a user's browsing history, which can be inferred by search engines via third-party tracking. Specifically, we develop a “sock puppet" auditing system in which a pair of fresh browser profiles, first, visits web pages that reflect divergent political discourses and, second, executes identical politically oriented Google News searches. Comparing the search results returned by Google News for distinctly trained browser profiles, we observe statistically significant personalization that tends to reinforce the presumed partisanship.

AB - There is a growing concern about the extent to which algorithmic personalization limits people's exposure to diverse viewpoints, thereby creating “filter bubbles" or “echo chambers." Prior research on web search personalization has mainly reported location-based personalization of search results. In this paper, we investigate whether web search results are personalized based on a user's browsing history, which can be inferred by search engines via third-party tracking. Specifically, we develop a “sock puppet" auditing system in which a pair of fresh browser profiles, first, visits web pages that reflect divergent political discourses and, second, executes identical politically oriented Google News searches. Comparing the search results returned by Google News for distinctly trained browser profiles, we observe statistically significant personalization that tends to reinforce the presumed partisanship.

UR - http://www.scopus.com/inward/record.url?scp=85066889419&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85066889419&partnerID=8YFLogxK

U2 - 10.1145/3308558.3312504

DO - 10.1145/3308558.3312504

M3 - Conference contribution

AN - SCOPUS:85066889419

T3 - The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019

SP - 2957

EP - 2963

BT - The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019

PB - Association for Computing Machinery, Inc

ER -

Le H, High A, Maragh R, Havens T, Ekdale B, Shafiq Z. Measuring political personalization of Google news search. In The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019. Association for Computing Machinery, Inc. 2019. p. 2957-2963. (The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019). https://doi.org/10.1145/3308558.3312504