Search Engine Bias and the Demise of Search Engine Utopianism
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Although users tend to select among the first results returned by the search engine, the interface enables them to browse many alternative results.
“Although users tend to select among the first results returned by the search engine (56), the interface enables them to browse many alternative results.”
From The impact of generative artificial intelligence on socioeconomic inequalities and policy making (2024) · cites this paper as [56]
Cites
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The ethics of algorithms: Mapping the debate
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“…as Eric Goldman, argue that the algorithmic manipulation of general search engine results need not concern us because the efficient functioning of markets will ensure that alternative search engines will emerge to provide algorithmic evaluations that better meet individual needs (Goldman, 2006).”
Bias in algorithmic filtering and personalization
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“For instance search engines make manual adjustments of a web publisher's overall rating or modify search results presented in response to particular keyword searches (Goldman 2005).”
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BackgroundThe impact of generative artificial intelligence on socioeconomic inequalities and policy making
Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J.-F., Brañas-Garza, P., Butera, L., Douglas, K. M., et al. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae191 · Cited by 371 · see citing works
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“Goldman (2005) notes that biases in search results against competitors could also lead to antitrust concerns for Google, even in the presence of substantial competition in the advertising market.”
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“On a theoretical level, content bias and diversity are legitimate and important issues and have been addressed from a policy perspective (Gasser 2006; Goldman 2006; Grimmelman 2007).”
BackgroundThe seventeen theoretical constructs of information searching and information retrieval
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“Similarly, several researchers have commented on the inherent biases of search engines (e.g., Goldman, 2006; Introna & Nissenbaum, 2000).”
BackgroundThe Debate on the Moral Responsibilities of Online Service Providers
Taddeo, M., & Floridi, L. (2016) · Science and Engineering Ethics · doi:10.1007/s11948-015-9734-1 · Cited by 141 · see citing works
“OSPs’ editorial role is also analysed in Goldman (2006).”
BackgroundMethodCoverage of emerging technologies: A comparison between print and online media
Cacciatore, M., Anderson, A. A., Choi, D., Brossard, D., Scheufele, D., Liang, X., Ladwig, P. J., Xenos, M., & Dudo, A. (2012) · New Media & Society · doi:10.1177/1461444812439061 · Cited by 119 · see citing works
“In other words, just because a person can search for multiple viewpoints about an issue, he or she may only realistically run across certain themes, due in part to editorial bias imposed on search engine results (Goldman, 2008).”
BackgroundModelling opinion dynamics in the age of algorithmic personalisation
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Beyond the Bubble: Assessing the Diversity of Political Search Results
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“For example, search can be seen as an engineering challenge to optimize precision and recall, yet it is important to realize that rankings can also have embedded values with social or political ramifications [23].”
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“For example, users of search engines have expressed concerns about biased and discriminatory search results (cf. Goldman, 2005; Noble, 2013); users of chatbots and other such AI-based service tools are concerned about the lack of interpersonal respect and care (cf. Barnett et al., 2021); and users…”
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“Although users rarely move beyond the first page of a search engine’s results (Goldman, 2008), the interface still enables browsing into a large number of results.”
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“This search bias allegation (see, e.g., Goldman, 2006; Ammori and Pelican, 2012; Edelman, 2011; Crane, 2011) has – by and large – been the key of the antitrust investigations against Google (see FTC 2013, European Commission, 2015).”
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The History of the Internet Search Engine: Navigational Media and the Traffic Commodity
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“Source: Author analysis Data on ISP rank and subscriber numbers from Goldman (2006) and reflect Q1 2006 status.”
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“Even by establishing ‘relevance’ as a key factor, search engine companies impact the distribution of results (Goldman, 2008).”
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“However, one may argue that generating bias—that is, introducing rules, systematically weighting certain factors over others and thus preferring some items—is the “core” concept of a search engine (Lewandowski, 2017, p. 67; see also Goldman, 2008).”
BackgroundThe Use and Misuse of Biomedical Data: Is Bigger Really Better?
Hoffman, S., & Podgurski, A. (2013) · American Journal of Law & Medicine · doi:10.1177/009885881303900401 · Cited by 59 · see citing works
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“More recent empirical evidence shows, for instance, that there are gaps in access to information across communities, in part due to the information needs of certain communities being less supported than those of others—often the more dominant communities (Goldman, 2005; Spink and Zimmer, 2008; Mehrotra et al., 2017; G…”
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Belief Dynamics and Biases in Web Search
White, R. W., & Horvitz, E. (2015) · ACM Transactions on Information Systems · doi:10.1145/2746229 · Cited by 49 · see citing works
Content Bias in Online Health Search
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“These algorithms can exhibit skew in the information that they cover [Gerhart 2004; Vaughan and Thelwall 2004; Goldman 2006] and in how they decide to order their search results [Mowshowitz and Kawaguchi 2002a, 2002b].”
BackgroundMcNally, S. L., Donohue, M., Newton, K. P., Ogletree, S. P., Conner, K. K., Ingegneri, S. E., & Kagnoff, M. F. (2012) · Interactive Journal of Medical Research · doi:10.2196/ijmr.2010 · Cited by 48 · see citing works
“This can lead to search engine bias [23].”
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“Because of the structure of search algorithms, the most prominent cancer blogs are those that have connections to mainstream media or high traffic sites, news or broadcast media (Butler 2000; Goldman 2006).”
BackgroundEvaluation metrics for measuring bias in search engine results
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“These statistics indicate that search engines replaced traditional broadcast media and have become amajor source of information B Gizem Gezici gizemgezici@sabanciuniv.edu 1 Department of Computer Science and Engineering, Sabanci University, Istanbul, Turkey 2 Department of Computer Science, University College London,…”
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“That research has focused on topically skewed result sets (Fortunato, Flammini, Menczer, & Vespignani, 2006; Goldman, 2006), or the impact of rank position, captions, or domain preferences on search-result selection (Ieong, Mishra, Sadikov, & Zhang, 2012; Joachims et al., 2007; Yue, Patel, &…”
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“Like Elkin-Koren, Chandler proposes a mix of regulatory and legislative approaches to address her concerns and protect the flow of information mediated by web search engines. Goldman (2006) , however, disagrees.”
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“In fact, people using web search engines assume that search results from search engines are unbiased and neutral [4].”
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“For instance, some scholars (e.g. Feuz, Fuller, & Stalder, 2011; Goldman, 2005) have argued that personalized information consumption would mitigate search engine bias, but such arguments have not been strongly supported by empirical analyses (e.g. Jiang, 2014a).”
BackgroundCaptions and biases in diagnostic search
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“However, search engine ranking algorithms can exhibit biases in the information that they cover [Gerhart 2004; Vaughan and Thelwall 2004; Goldman 2006] and how they choose to order their results [Mowshowitz and Kawaguchi 2002a, 2002b], have limited access to information about a searcher s…”
BackgroundWho are interested in online science simulations? Tracking a trend of digital divide in Internet use
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“The first website in the search results enjoys a “winner-take-all” effect (Goldman, 2008), and receives 33% of total traffic generated by the search (Chitika, 2013).”
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Bubble Trouble: Strategies Against Filter Bubbles in Online Social Networks
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BackgroundImproving search ranking of geospatial data based on deep learning using user behavior data
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“As “search engine bias” that skews search results can affect information seeking and retrieval (Goldman, 2005), future research may examine what kinds of biases exist in locative technology and how they shape urban learning processes.”
BackgroundSearch engine predilection towards news media providers
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“In this sense, Google shows the most popular and frequent visited-sites before less popular sites, thus contributing to the success of the more visited ones (Goldman, 2008).”
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“Thus scholars within this paradigm have critiqued search engines operating within the market paradigm because results may include mainstream Web pages at the expense of smaller sites containing important information for citizens (Goldman, 2008; Introna & Nissenbaum, 2000; Van Couvering, 2008).”
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“Search bias refers to a situation where the search results systematically favor certain types of content over others (Goldman 2008).”
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“Scholars have discussed and found present biases in online media such as skewed search results (Goldman, 2008) or gender difference in STEM career ads (Lambrecht and Tucker, 2019), yet little has been known about mechanisms or origins of such biases.”
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Control search rankings, control the world: what is a good search engine?
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“It may be countered that inferring user intentions can be inaccurate (and paternalistic), and risks introducing biases from the system [32].”
Fair‐y Tales: An analysis of children’s books about sun safety
McCormack, L., Dzuali, F., Tappel, A. C., & Huang, J. T. (2020) · Pediatric Dermatology · doi:10.1111/pde.14387 · Cited by 7 · see citing works
The Mereology of Digital Copyright
Burk, D. L. (2006) · Springer eBooks · doi:10.1007/978-1-4020-9789-8_7 · Cited by 7 · see citing works
“Increased access to such digitized works has heightened the need for robust systems that can identify and index online resources, in order to allow users to locate and access the new wealth of digitized materials in what amounts to a global virtual library ( Goldman, 2006 ).”
BackgroundNatale, S. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780190080365.003.0004 · Cited by 7 · see citing works
Mottos and Ethical Statements of Internet-Based Organizations
Oravec, J. A. (2014) · International Journal of Civic Engagement and Social Change · doi:10.4018/ijcesc.2014040103 · Cited by 7 · see citing works
Kerssens, N. (2017) · Internet Histories · doi:10.1080/24701475.2017.1337666 · Cited by 7 · see citing works
“…have challenged assumptions about engines as neutral and objective information intermediaries, revealing how they incorporate biases (Diaz, 2008; Goldman, 2006; Introna & Nissenbaum, 2000; Jiang, 2014; Mowshowitz & Kawaguchi, 2002); actively produce information and knowledge through mechanisms…”
BackgroundDuclos, V. (2019) · Medicine Anthropology Theory · doi:10.17157/mat.6.3.660 · Cited by 9 · see citing works
Sender vs. recipient-orientated information systems revisited
MacFarlane, A., Missaoui, S., Makri, S., & Lopez, M. G. (2021) · Journal of Documentation · doi:10.1108/jd-10-2020-0177 · Cited by 7 · see citing works
Infodemiology of Alcohol Use in Hong Kong Mentioned on Blogs: Infoveillance Study
Chan, K.-L. L., Ho, S. Y., & Lam, T. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2180 · Cited by 6 · see citing works
Political Conflicts around the Internet in Russia: The Case of Yandex.Novosti
Daucé, F. (2017) · Laboratorium Russian Review of Social Research · doi:10.25285/2078-1938-2017-9-2-112-132 · Cited by 6 · see citing works
Singh, I., Naci, H., Miller, J. E., Caplan, A. L., & Cipriani, A. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30413-x · Cited by 6 · see citing works
“Algorithms have also been criticised for perpetuating other biases found in science, including racial, ethnic and gender biases.(6) The ‘black box’ of the machine-learning algorithm means that clinicians cannot judge the strength or applicability of the evidence that is provided to inform decisions in the clinic.”
BackgroundBias in Text Generative Open AI
Devisetti, S. A. (2024) · Indian Journal of Artificial Intelligence and Neural Networking · doi:10.54105/ijainn.b1084.04020224 · Cited by 5 · see citing works
Page Ranking Refinement Using Fuzzy Sets and Logic.
Laughlin, A. J., Olson, J., Simpson, D., & Inoue, A. (2011) · Cited by 4 · see citing works
Users’ Perception of Search-Engine Biases and Satisfaction
Han, B., Shah, C. S., & Saelid, D. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-78818-6_3 · Cited by 4 · see citing works
Olteanu, A., Garcia-Gathright, J., de Rijke, M., & Ekstrand, M. D. (2019) · Annual International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3331184.3331644 · Cited by 13 · see citing works
“More recent empirical evidence shows, for instance, that there are gaps in access to information across communities, in part due to the information needs of certain communities being less supported than those of others—often the more dominant communities [6, 9, 13, 14].”
BackgroundAlgorithmic logics of taste: Cultural taste and the Netflix recommender system
Gaw, F. (2019) · The Sydney eScholarship Repository (The University of Sydney) · Cited by 4 · see citing works
Analyzing the content emphasis of web search engines
Alam, M. A., & Downey, D. (2014) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2600428.2609515 · Cited by 3 · see citing works
“Legal scholars have debated whether search engines should be regulated to ensure “neutrality” [3, 7].”
BackgroundEthical concerns of search technology: search engine bias
Pastierová, M. (2022) · ProInflow Časopis pro informační vědy · doi:10.5817/proin2022-2-9 · Cited by 3 · see citing works
“Don't Be Evil” and Beyond for High Tech Organizations
Oravec, J. A. (2018) · Advances in human and social aspects of technology book series · doi:10.4018/978-1-5225-4197-4.ch013 · Cited by 3 · see citing works
- Authors
- Goldman, E.
- Affiliations
- Santa Clara University (US)
- Corresponding author
- Goldman, E.
- ORCID
- Goldman, E.
- Venue
- Information Science and Knowledge Management
- Publisher
- Springer Berlin Heidelberg
- Published
- 2008
- Pages
- 121-133
- ISSN
- 1568-1300 (ISSN-L)
- OpenAlex
- W1670552626
- Cited by
- 166
- References
- 13
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 3 · 2023: 24 · 2022: 4 · 2021: 24 · 2020: 12 · 2019: 13 · 2018: 8 · 2017: 5 · 2016: 9 · 2015: 8 · 2014: 12 · 2013: 13 · 2012: 4
- FWCI
- 18.45
- Type
- book chapter
- Language
- en
- Open access
- green
- papers.ssrn.com
- Locations
- Information science and knowledge management (publishedVersion)
- Santa Clara Law Digital Commons (Santa Clara University) (submittedVersion)
- bepress Legal Repository (submittedVersion)
- SSRN Electronic Journal (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Keywords
- search engine bias, search engine optimization, personalized search, search engine regulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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