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
N1 - Publisher Copyright:
© 2019 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License.
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.
KW - Google
KW - Measurement
KW - News
KW - Personalization
KW - Search
UR - http://www.scopus.com/inward/record.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
T2 - 2019 World Wide Web Conference, WWW 2019
Y2 - 13 May 2019 through 17 May 2019
ER -