The Relevance of Algorithms
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
These mechanisms shape hierarchies of relevance and authority while embedding commercial logics, including advertising revenue optimization and self-preferencing practices, directly into the ordering of knowledge.
“Together, these mechanisms shape hierarchies of relevance and authority while embedding commercial logics (Gillespie, 2014; Pasquinelli, 2009), including advertising revenue optimization and self-preferencing practices (Bougette et al., 2022; Modi and Modi, 2024), directly into the ordering of knowledge.”
From Google Arts & Culture and the platformization of cultural heritage: Convergence, gamification, and shifting positions of institutional partners (2026) · cites this paper as Gillespie, 2014
Algorithms are now communication technology and scientific instruments of a society at large.
“As Gillespie (2014, p. 169) puts it, these 'are now communication technology; like broadcasting and publishing technologies, they are now 'the scientific instruments of a society at large.'”
From Recalling McLuhan: The Power of Netflix and Digital Platforms in the Age of Digital Capitalism (2026) · cites this paper as Gillespie, 2014
Critical algorithm studies emphasize that such systems operate as cultural and institutional mediators rather than neutral instruments.
“Critical algorithm studies emphasize that such systems operate as cultural and institutional mediators rather than neutral instruments [2,14].”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [14]
Research on social transparency and algorithmic accountability shows that trust in AI systems emerges from explanations embedded within organizational and cultural contexts rather than from technical interpretability alone.
“Research on social transparency and algorithmic accountability shows that trust in AI systems emerges from explanations embedded within organizational and cultural contexts rather than from technical interpretability alone [12,14].”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [14]
Cites
Hutchins, E. (1995) · doi:10.7551/mitpress/1881.001.0001 · Cited by 10,801 · see citing works
Gillespie, T. (2010) · New Media & Society · doi:10.1177/1461444809342738 · Cited by 2,522 · cited 1× · see citing works
“…várias audiências, às vezes de várias formas diferentes: um algoritmo pode ser defendido como uma ferramenta de avaliação imparcial para os críticos dos seus resultados e, ao mesmo tempo, ser prometido como uma ferramenta para a promoção seletiva e para anunciantes em potencial (GILLESPIE, 2010).”
BackgroundSelf-citationSocial Network Sites as Networked Publics: Affordances, Dynamics, and Implications
(2010) · A Networked Self · doi:10.4324/9780203876527-8 · Cited by 1,724 · cited 2× · see citing works
“Ito, Boyd e outros autores recentemente introduziram o termo “públicos em rede” (BOYD, 2010; ITO, 2008; VARNELIS, 2008) para destacar as comunidades de usuários que podem se unir através das mídias sociais e a forma como as tecnologias estruturam como esses públicos podem se formar, interagir e, às…”
BackgroundA New Algorithmic Identity: Soft Biopolitics and the Modulation of Control
Cheney-Lippold, J. (2011) · Theory, Culture & Society · doi:10.1177/0263276411424420 · Cited by 684 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
How the machine “thinks”: Understanding opacity in machine learning algorithms
Burrell, J. (2016) · Big Data & Society · doi:10.1177/2053951715622512 · Cited by 3,196 · see citing works
“(Gillespie, 2012) The goal of this article was to look more deeply into machine learning algorithms and the nature of their ‘opacity’, relating this to sociological interests in classi-fication and discrimination.”
BackgroundAlgorithms at Work: The New Contested Terrain of Control
Kellogg, K. C., Valentine, M. A., & Christin, A. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0174 · Cited by 2,732 · see citing works
Artificial Intelligence and Management: The Automation–Augmentation Paradox
Raisch, S., & Krakowski, S. (2021) · Academy of Management Review · doi:10.5465/amr.2018.0072 · Cited by 2,755 · see citing works
Ananny, M., & Crawford, K. (2018) · New Media & Society · doi:10.1177/1461444816676645 · Cited by 1,836 · see citing works
If...Then: Algorithmic Power and Politics
Bucher, T. (2018) · doi:10.1093/oso/9780190493028.001.0001 · Cited by 1,223 · see citing works
In AI we trust? Perceptions about automated decision-making by artificial intelligence
Araujo, T., Helberger, N., Kruikemeier, S., & de Vreese, C. H. (2020) · AI & SOCIETY · doi:10.1007/s00146-019-00931-w · Cited by 1,038 · see citing works
Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram
Cotter, K. (2019) · New Media & Society · doi:10.1177/1461444818815684 · Cited by 1,025 · see citing works
Algorithmic regulation: A critical interrogation
Yeung, K. (2018) · Regulation & Governance · doi:10.1111/rego.12158 · Cited by 842 · see citing works
Algorithmic Accountability: Journalistic investigation of computational power structures
Diakopoulos, N. (2015) · Digital Journalism · doi:10.1080/21670811.2014.976411 · Cited by 733 · see citing works
Lepri, B., Oliver, N., Letouzé, E., Pentland, A., & Vinck, P. (2018) · Philosophy & Technology · doi:10.1007/s13347-017-0279-x · Cited by 709 · see citing works
Artificial intelligence and illusions of understanding in scientific research
Messeri, L., & Crockett, M. J. (2024) · Nature · doi:10.1038/s41586-024-07146-0 · Cited by 707 · see citing works
Lebovitz, S., Lifshitz-Assaf, H., & Levina, N. (2022) · Organization Science · doi:10.1287/orsc.2021.1549 · Cited by 632 · see citing works
Carlson, M. (2015) · Digital Journalism · doi:10.1080/21670811.2014.976412 · Cited by 542 · see citing works
New games, new rules: big data and the changing context of strategy
Constantiou, I. D., & Kallinikos, J. (2015) · Journal of Information Technology · doi:10.1057/jit.2014.17 · Cited by 526 · see citing works
Algorithms and their others: Algorithmic culture in context
Dourish, P. (2016) · Big Data & Society · doi:10.1177/2053951716665128 · Cited by 481 · see citing works
Algorithms as work designers: How algorithmic management influences the design of jobs
Parent-Rocheleau, X., & Parker, S. K. (2022) · Human Resource Management Review · doi:10.1016/j.hrmr.2021.100838 · Cited by 512 · see citing works
Explanations as Mechanisms for Supporting Algorithmic Transparency
Rader, E., Cotter, K., & Cho, J. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173677 · Cited by 388 · see citing works
Understanding User Beliefs About Algorithmic Curation in the Facebook News Feed
Rader, E., & Gray, R. (2015) · Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702174 · Cited by 386 · see citing works
Social Media, Echo Chambers, and Political Polarization
Barberá, P. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.004 · Cited by 373 · see citing works
Between autonomy and control: Strategies of arbitrage in the “on-demand” economy
Shapiro, A. (2018) · New Media & Society · doi:10.1177/1461444817738236 · Cited by 374 · see citing works
The challenges and limits of big data algorithms in technocratic governance
Janssen, M., & Kuk, G. (2016) · Government Information Quarterly · doi:10.1016/j.giq.2016.08.011 · Cited by 363 · see citing works
The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity
Leicht-Deobald, U., Busch, T., Schank, C., Weibel, A., Schafheitle, S., Wildhaber, I., & Kasper, G. (2019) · Journal of Business Ethics · doi:10.1007/s10551-019-04204-w · Cited by 347 · see citing works
DeVito, M. A., Birnholtz, J., Hancock, J. T., French, M., & Liu, S. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173694 · Cited by 244 · see citing works
Auditing Partisan Audience Bias within Google Search
Robertson, R. E., Jiang, S., Joseph, K., Friedland, L., Lazer, D., & Wilson, C. (2018) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3274417 · Cited by 209 · see citing works
Automation, APIs and the distributed labour of platform pedagogies in google classroom
Perrotta, C., Gulson, K. N., Williamson, B., & Witzenberger, K. (2021) · Critical Studies in Education · doi:10.1080/17508487.2020.1855597 · Cited by 208 · see citing works
Anthony, C. (2021) · Administrative Science Quarterly · doi:10.1177/00018392211016755 · Cited by 191 · see citing works
Development and Validation of an Algorithm Literacy Scale for Internet Users
Dogruel, L., Masur, P., & Joeckel, S. (2022) · Communication Methods and Measures · doi:10.1080/19312458.2021.1968361 · Cited by 177 · see citing works
Andrews, L. (2019) · Public Administration · doi:10.1111/padm.12534 · Cited by 172 · see citing works
Buhmann, A., Paßmann, J., & Fieseler, C. (2020) · Journal of Business Ethics · doi:10.1007/s10551-019-04226-4 · Cited by 167 · see citing works
Algorithmic Authority: The Case of Bitcoin
Lustig, C., & Nardi, B. (2015) · 2015 48th Hawaii International Conference on System Sciences · doi:10.1109/hicss.2015.95 · Cited by 166 · see citing works
Marda, V. (2018) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2018.0087 · Cited by 161 · see citing works
Cotter, K. (2023) · Information, Communication & Society · doi:10.1080/1369118x.2021.1994624 · Cited by 149 · see citing works
Liable, but not in control? Ensuring meaningful human agency in automated decision-making systems
Wagner, B. (2019) · Policy & Internet · doi:10.1002/poi3.198 · Cited by 136 · see citing works
The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good
Lepri, B., Staiano, J., Sangokoya, D., Letouzé, E., & Oliver, N. (2017) · Studies in Big Data · doi:10.1007/978-3-319-54024-5_1 · Cited by 111 · see citing works
Algorithmic IF … THEN rules and the conditions and consequences of power
Neyland, D., & Möllers, N. (2017) · Information, Communication & Society · doi:10.1080/1369118x.2016.1156141 · Cited by 108 · see citing works
Big Data and algorithmic governance: The case of financial practices
Campbell-Verduyn, M., Goguen, M., & Porter, T. (2017) · New Political Economy · doi:10.1080/13563467.2016.1216533 · Cited by 99 · see citing works
Persuasive computing: Feeling peer pressure from multiple computer agents
Xu, K., & Lombard, M. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.04.043 · Cited by 76 · see citing works
Algorithms as fetish: Faith and possibility in algorithmic work
Thomas, S. L., Nafus, D., & Sherman, J. (2018) · Big Data & Society · doi:10.1177/2053951717751552 · Cited by 72 · see citing works
Proceduralizing control and discretion: Human oversight in artificial intelligence policy
Koulu, R. (2020) · Maastricht Journal of European and Comparative Law · doi:10.1177/1023263x20978649 · Cited by 72 · see citing works
Automated Decision-Making and Big Data: Concerns for People With Mental Illness
Monteith, S., & Glenn, T. (2016) · Current Psychiatry Reports · doi:10.1007/s11920-016-0746-6 · Cited by 62 · see citing works
Psychoanalyzing artificial intelligence: the case of Replika
Possati, L. M. (2023) · AI & SOCIETY · doi:10.1007/s00146-021-01379-7 · Cited by 65 · see citing works
Cotter, K., Medeiros, M., Pak, C., & Thorson, K. (2021) · Big Data & Society · doi:10.1177/2053951721996046 · Cited by 63 · see citing works
Algorithmic memory and the right to be forgotten on the web
Esposito, E. (2017) · Big Data & Society · doi:10.1177/2053951717703996 · Cited by 61 · see citing works
The return of the social: Algorithmic identity in an age of symbolic demise
Kotliar, D. M. (2020) · New Media & Society · doi:10.1177/1461444820912535 · Cited by 45 · see citing works
Memeingful memories and the art of resistance
Silvestri, L. E. (2018) · New Media & Society · doi:10.1177/1461444818766092 · Cited by 40 · see citing works
Huang, Y., & Ye, W. (2024) · Convergence: The International Journal of Research into New Media Technologies · doi:10.1177/13548565231211117 · Cited by 37 · see citing works
Expanding on the Frames: Making a Case for Algorithmic Literacy
Loyola Marymount University, & Archambault, S. (2023) · Communications in Information Literacy · doi:10.15760/comminfolit.2023.17.2.11 · Cited by 19 · see citing works
Joanroy, T., Steenvoorden, E., Padure, D., Venger, R., & Smit, R. (2025) · Memory, Mind & Media · doi:10.1017/mem.2025.4 · Cited by 4 · see citing works
Ahmad, H., & Ghafar, N. A. (2026) · AI and Ethics · doi:10.1007/s43681-026-01254-5 · Cited by 3 · see citing works
Cao, T. L. (2025) · Platforms & Society · doi:10.1177/29768624251349092 · Cited by 3 · see citing works
Cao, T. L. (2026) · Convergence: The International Journal of Research into New Media Technologies · doi:10.1177/13548565261431167
Recalling McLuhan: The Power of Netflix and Digital Platforms in the Age of Digital Capitalism
Altınkaya, M. T. (2026) · Kent Akademisi · doi:10.35674/kent.1750355
- Authors
- Gillespie, T.
- Corresponding author
- Gillespie, Tarleton
- ORCID
- Gillespie, Tarleton
- Venue
- Media Technologies
- Publisher
- The MIT Press
- Published
- 2014-01-17
- Pages
- 167-194
- OpenAlex
- W4391374907
- Cited by
- 1,016
- References
- 4
- Citations by year
- 2026: 287 · 2025: 138 · 2024: 85 · 2023: 100 · 2022: 97 · 2021: 42 · 2020: 87 · 2019: 48 · 2018: 39 · 2017: 33 · 2016: 32 · 2015: 19 · 2014: 9
- FWCI
- 81.77
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- The MIT Press eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computability, Logic, AI Algorithms
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Cybernetics and Technology in Society
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Complexity and Algorithms in Graphs
- Keywords
- algorithms
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 ›
Are you an author, or do you see a problem with this page? Request a review
