Algorithmic bias (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Algorithmic bias" in English language version.

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73doi.org

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accessnow.org (Global: low place; English: low place)

The Toronto Declaration: Protecting the Right to Equality and Non-Discrimination in Machine Learning Systems (PDF). Human Rights Watch. 2018. p. 15.

aclanthology.org (Global: low place; English: low place)

Friðriksdóttir, Steinunn Rut; Einarsson, Hafsteinn (2024), "Gendered Grammar or Ingrained Bias? Exploring Gender Bias in Icelandic Language Models", Lrec-Coling 2024: 7596–7610
Feng, Shangbin; Park, Chan Young; Liu, Yuhan; Tsvetkov, Yulia (July 2023). Rogers, Anna; Boyd-Graber, Jordan; Okazaki, Naoaki (eds.). "From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models". Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Toronto, Canada: Association for Computational Linguistics: 11737–11762. arXiv:2305.08283. doi:10.18653/v1/2023.acl-long.656.

acm.org (Global: 1,185^th place; English: 840^th place)

dl.acm.org

Suresh, Harini; Guttag, John (November 4, 2021). "A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle". Equity and Access in Algorithms, Mechanisms, and Optimization. EAAMO '21. New York, NY, USA: Association for Computing Machinery. pp. 1–9. doi:10.1145/3465416.3483305. ISBN 978-1-4503-8553-4. S2CID 235436386.
Mehrabi, N.; Morstatter, F.; Saxena, N.; Lerman, K.; Galstyan, A. (2021). "A survey on bias and fairness in machine learning". ACM Computing Surveys. 54 (6): 1–35. arXiv:1908.09635. doi:10.1145/3457607. Retrieved April 30, 2025.
Busker, Tony; Choenni, Sunil; Shoae Bargh, Mortaza (November 20, 2023). "Stereotypes in ChatGPT: An empirical study". Proceedings of the 16th International Conference on Theory and Practice of Electronic Governance. ICEGOV '23. New York, NY, USA: Association for Computing Machinery. pp. 24–32. doi:10.1145/3614321.3614325. ISBN 979-8-4007-0742-1.
Kotek, Hadas; Dockum, Rikker; Sun, David (November 5, 2023). "Gender bias and stereotypes in Large Language Models". Proceedings of the ACM Collective Intelligence Conference. CI '23. New York, NY, USA: Association for Computing Machinery. pp. 12–24. arXiv:2308.14921. doi:10.1145/3582269.3615599. ISBN 979-8-4007-0113-9.
Raji, Inioluwa Deborah; Gebru, Timnit; Mitchell, Margaret; Buolamwini, Joy; Lee, Joonseok; Denton, Emily (February 7, 2020). "Saving Face". Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. Association for Computing Machinery. pp. 145–151. arXiv:2001.00964. doi:10.1145/3375627.3375820. ISBN 978-1-4503-7110-0. S2CID 209862419.
Chen, Jiahao; Kallus, Nathan; Mao, Xiaojie; Svacha, Geoffry; Udell, Madeleine (2019). "Fairness Under Unawareness". Proceedings of the Conference on Fairness, Accountability, and Transparency. Atlanta, GA, USA: ACM Press. pp. 339–348. arXiv:1811.11154. doi:10.1145/3287560.3287594. ISBN 978-1-4503-6125-5. S2CID 58006233.
Mitchell, Margaret; Wu, Simone; Zaldivar, Andrew; Barnes, Parker; Vasserman, Lucy; Hutchinson, Ben; Spitzer, Elena; Raji, Inioluwa Deborah; Gebru, Timnit (January 29, 2019). "Model Cards for Model Reporting". Proceedings of the Conference on Fairness, Accountability, and Transparency. ACM. pp. 220–229. arXiv:1810.03993. doi:10.1145/3287560.3287596. ISBN 978-1-4503-6125-5.
Gebru, Timnit; Morgenstern, Jamie; Vecchione, Briana; Vaughan, Jennifer Wortman; Wallach, Hanna; Iii, Hal Daumé; Crawford, Kate (December 2021). "Datasheets for datasets". Communications of the ACM. 64 (12): 86–92. arXiv:1803.09010. doi:10.1145/3458723. ISSN 0001-0782.

ainowinstitute.org (Global: low place; English: low place)

Whittaker, Meredith (November 2019). "Disability, Bias, and AI" (PDF). Archived from the original (PDF) on March 27, 2023. Retrieved December 2, 2022.

allthingsd.com (Global: 7,373^rd place; English: 4,987^th place)

Kafka, Peter. "Did Amazon Really Fail This Weekend? The Twittersphere Says 'Yes,' Online Retailer Says 'Glitch.'". AllThingsD. Retrieved November 22, 2017.
Kafka, Peter. "Amazon Apologizes for 'Ham-fisted Cataloging Error'". AllThingsD. Retrieved November 22, 2017.

ampproject.org (Global: 2,221^st place; English: low place)

venturebeat-com.cdn.ampproject.org

Johnson, Khari (May 31, 2018). "Pymetrics open-sources Audit AI, an algorithm bias detection tool". VentureBeat.com.

archive.org (Global: 6^th place; English: 6^th place)

Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford (2009). Introduction to Algorithms (3rd ed.). Cambridge, Mass.: MIT Press. p. 5. ISBN 978-0-262-03384-8.
Weizenbaum, Joseph (1976). Computer Power and Human Reason: From Judgment to Calculation. San Francisco: W.H. Freeman. ISBN 978-0-7167-0464-5.
Goffrey, Andrew (2008). "Algorithm". In Fuller, Matthew (ed.). Software Studies: A Lexicon. Cambridge, Mass.: MIT Press. pp. 15–20. ISBN 978-1-4356-4787-9.

archives.gov (Global: 446^th place; English: 308^th place)

obamawhitehouse.archives.gov

Obama, Barack (October 12, 2016). "The Administration's Report on the Future of Artificial Intelligence". whitehouse.gov. National Archives. Retrieved November 26, 2017.
and Technology Council, National Science (2016). National Artificial Intelligence Research and Development Strategic Plan (PDF). US Government. Retrieved November 26, 2017.

arxiv.org (Global: 69^th place; English: 59^th place)

Mehrabi, N.; Morstatter, F.; Saxena, N.; Lerman, K.; Galstyan, A. (2021). "A survey on bias and fairness in machine learning". ACM Computing Surveys. 54 (6): 1–35. arXiv:1908.09635. doi:10.1145/3457607. Retrieved April 30, 2025.
Goodman, Bryce; Flaxman, Seth (2017). "EU regulations on algorithmic decision-making and a "right to explanation"". AI Magazine. 38 (3): 50. arXiv:1606.08813. doi:10.1609/aimag.v38i3.2741. S2CID 7373959.
Luo, Queenie; Puett, Michael J.; Smith, Michael D. (May 23, 2023), A Perspectival Mirror of the Elephant: Investigating Language Bias on Google, ChatGPT, Wikipedia, and YouTube, arXiv:2303.16281
Choi, Hyeong Kyu; Xu, Weijie; Xue, Chi; Eckman, Stephanie; Reddy, Chandan K. (September 27, 2024), Mitigating Selection Bias with Node Pruning and Auxiliary Options, arXiv:2409.18857
Zheng, Chujie; Zhou, Hao; Meng, Fandong; Zhou, Jie; Huang, Minlie (September 7, 2023), Large Language Models Are Not Robust Multiple Choice Selectors, arXiv:2309.03882
Kotek, Hadas; Dockum, Rikker; Sun, David (November 5, 2023). "Gender bias and stereotypes in Large Language Models". Proceedings of the ACM Collective Intelligence Conference. CI '23. New York, NY, USA: Association for Computing Machinery. pp. 12–24. arXiv:2308.14921. doi:10.1145/3582269.3615599. ISBN 979-8-4007-0113-9.
Cheng, Myra; Durmus, Esin; Jurafsky, Dan (May 29, 2023), Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models, arXiv:2305.18189
Wang, Angelina; Morgenstern, Jamie; Dickerson, John P. (February 17, 2025). "Large language models that replace human participants can harmfully misportray and flatten identity groups". Nature Machine Intelligence. 7 (3): 400–411. arXiv:2402.01908. doi:10.1038/s42256-025-00986-z.
Feng, Shangbin; Park, Chan Young; Liu, Yuhan; Tsvetkov, Yulia (July 2023). Rogers, Anna; Boyd-Graber, Jordan; Okazaki, Naoaki (eds.). "From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models". Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Toronto, Canada: Association for Computational Linguistics: 11737–11762. arXiv:2305.08283. doi:10.18653/v1/2023.acl-long.656.
Prates, Marcelo O. R.; Avelar, Pedro H. C.; Lamb, Luis (2018). "Assessing Gender Bias in Machine Translation -- A Case Study with Google Translate". arXiv:1809.02208 [cs.CY].
Prates, Marcelo O. R.; Avelar, Pedro H.; Lamb, Luís C. (2019). "Assessing gender bias in machine translation: A case study with Google Translate". Neural Computing and Applications. 32 (10): 6363–6381. arXiv:1809.02208. doi:10.1007/s00521-019-04144-6. S2CID 52179151.
Sweeney, Latanya (January 28, 2013). "Discrimination in Online Ad Delivery". arXiv:1301.6822 [cs.IR].
Raji, Inioluwa Deborah; Gebru, Timnit; Mitchell, Margaret; Buolamwini, Joy; Lee, Joonseok; Denton, Emily (February 7, 2020). "Saving Face". Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. Association for Computing Machinery. pp. 145–151. arXiv:2001.00964. doi:10.1145/3375627.3375820. ISBN 978-1-4503-7110-0. S2CID 209862419.
Morris, Meredith Ringel (May 22, 2020). "AI and accessibility". Communications of the ACM. 63 (6): 35–37. arXiv:1908.08939. doi:10.1145/3356727. ISSN 0001-0782. S2CID 201645229.
Castelnovo, Alessandro; Inverardi, Nicole; Nanino, Gabriele; Penco, Ilaria; Regoli, Daniele (2023). "Fair Enough? A map of the current limitations to the requirements to have "fair" algorithms". arXiv:2311.12435 [cs.AI].
Friedler, Sorelle A.; Scheidegger, Carlos; Venkatasubramanian, Suresh (2016). "On the (im)possibility of fairness". arXiv:1609.07236 [cs.CY].
Hu, Lily; Chen, Yiling (2018). "Welfare and Distributional Impacts of Fair Classification". arXiv:1807.01134 [cs.LG].
Dwork, Cynthia; Hardt, Moritz; Pitassi, Toniann; Reingold, Omer; Zemel, Rich (November 28, 2011). "Fairness Through Awareness". arXiv:1104.3913 [cs.CC].
Chen, Jiahao; Kallus, Nathan; Mao, Xiaojie; Svacha, Geoffry; Udell, Madeleine (2019). "Fairness Under Unawareness". Proceedings of the Conference on Fairness, Accountability, and Transparency. Atlanta, GA, USA: ACM Press. pp. 339–348. arXiv:1811.11154. doi:10.1145/3287560.3287594. ISBN 978-1-4503-6125-5. S2CID 58006233.
Kilbertus, Niki; Gascon, Adria; Kusner, Matt; Veale, Michael; Gummadi, Krishna; Weller, Adrian (2018). "Blind Justice: Fairness with Encrypted Sensitive Attributes". International Conference on Machine Learning: 2630–2639. arXiv:1806.03281. Bibcode:2018arXiv180603281K.
Binns, Reuben; Veale, Michael; Kleek, Max Van; Shadbolt, Nigel (September 13, 2017). "Like Trainer, Like Bot? Inheritance of Bias in Algorithmic Content Moderation". Social Informatics. Lecture Notes in Computer Science. Vol. 10540. pp. 405–415. arXiv:1707.01477. doi:10.1007/978-3-319-67256-4_32. ISBN 978-3-319-67255-7. S2CID 2814848.
Jobin, Anna; Ienca, Marcello; Vayena, Effy (September 2, 2019). "The global landscape of AI ethics guidelines". Nature Machine Intelligence. 1 (9): 389–399. arXiv:1906.11668. Bibcode:2019NatMI...1..389J. doi:10.1038/s42256-019-0088-2. S2CID 201827642.
Hardt, Moritz; Price, Eric; Srebro, Nathan (2016). "Equality of Opportunity in Supervised Learning". arXiv:1610.02413 [cs.LG].
Mitchell, Margaret; Wu, Simone; Zaldivar, Andrew; Barnes, Parker; Vasserman, Lucy; Hutchinson, Ben; Spitzer, Elena; Raji, Inioluwa Deborah; Gebru, Timnit (January 29, 2019). "Model Cards for Model Reporting". Proceedings of the Conference on Fairness, Accountability, and Transparency. ACM. pp. 220–229. arXiv:1810.03993. doi:10.1145/3287560.3287596. ISBN 978-1-4503-6125-5.
Gebru, Timnit; Morgenstern, Jamie; Vecchione, Briana; Vaughan, Jennifer Wortman; Wallach, Hanna; Iii, Hal Daumé; Crawford, Kate (December 2021). "Datasheets for datasets". Communications of the ACM. 64 (12): 86–92. arXiv:1803.09010. doi:10.1145/3458723. ISSN 0001-0782.
Bondi, Elizabeth; Xu, Lily; Acosta-Navas, Diana; Killian, Jackson A. (2021). "Envisioning Communities: A Participatory Approach Towards AI for Social Good". Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society. pp. 425–436. arXiv:2105.01774. doi:10.1145/3461702.3462612. ISBN 978-1-4503-8473-5. S2CID 233740121. Retrieved April 6, 2023 – via ezpa.library.ualberta.ca.
Bondi, Elizabeth; Xu, Lily; Acosta-Navas, Diana; Killian, Jackson A. (July 21, 2021). "Envisioning Communities: A Participatory Approach Towards AI for Social Good". Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society. pp. 425–436. arXiv:2105.01774. doi:10.1145/3461702.3462612. ISBN 978-1-4503-8473-5. S2CID 233740121.

bc.edu (Global: 4,784^th place; English: 3,078^th place)

lawdigitalcommons.bc.edu

Crawford, Kate; Schultz, Jason (2014). "Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms". Boston College Law Review. 55 (1): 93–128. Retrieved November 18, 2017.

books.google.com (Global: 3^rd place; English: 3^rd place)

Kubitschko, Sebastian; Kaun, Anne (2016). Innovative Methods in Media and Communication Research. Springer. ISBN 978-3-319-40700-5. Retrieved November 19, 2017.

brookings.edu (Global: 1,634^th place; English: 1,093^rd place)

"To stop algorithmic bias, we first have to define it". Brookings. Retrieved June 27, 2023.

channelnewsasia.com (Global: 1,127^th place; English: 691^st place)

"Commentary: Bad news. Artificial intelligence is biased". CNA. January 12, 2019. Archived from the original on January 12, 2019. Retrieved June 19, 2020.

columbia.edu (Global: 488^th place; English: 374^th place)

scholarship.law.columbia.edu

Harcourt, Bernard (September 16, 2010). "Risk as a Proxy for Race". Federal Sentencing Reporter. 27 (4): 237. doi:10.1525/fsr.2015.27.4.237. S2CID 53611813. SSRN 1677654.

computer.org (Global: 5,196^th place; English: 3,635^th place)

"Software & Systems Engineering Standards Committee". April 17, 2018.
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cornell.edu (Global: 332^nd place; English: 246^th place)

nissenbaum.tech.cornell.edu

Friedman, Batya; Nissenbaum, Helen (July 1996). "Bias in Computer Systems" (PDF). ACM Transactions on Information Systems. 14 (3): 330–347. doi:10.1145/230538.230561. S2CID 207195759. Retrieved March 10, 2019.

culturedigitally.org (Global: low place; English: low place)

Striphas, Ted (February 2012). "What is an Algorithm? – Culture Digitally". culturedigitally.org. Retrieved November 20, 2017.
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darpa.mil (Global: low place; English: 7,006^th place)

"Explainable Artificial Intelligence". www.darpa.mil. Retrieved February 11, 2020.

disabilityisdiversity.com (Global: low place; English: low place)

"Mission — Disability is Diversity — Dear Entertainment Industry, THERE'S NO DIVERSITY, EQUITY & INCLUSION WITHOUT DISABILITY". Disability is Diversity. Retrieved December 2, 2022.

doi.org (Global: 2^nd place; English: 2^nd place)

Hardebolle, Cécile; Héder, Mihály; Ramachandran, Vivek (November 25, 2024), "Engineering ethics education and artificial intelligence", The Routledge International Handbook of Engineering Ethics Education (1 ed.), London: Routledge, pp. 125–142, doi:10.4324/9781003464259-9, ISBN 978-1-003-46425-9
Van Eyghen, Hans (2025). "AI Algorithms as (Un)virtuous Knowers". Discover Artificial Intelligence. 5 (2) 2. doi:10.1007/s44163-024-00219-z.
Marabelli, Marco (2024). AI, Ethics, and Discrimination in Business. Palgrave Studies in Equity, Diversity, Inclusion, and Indigenization in Business. Springer. doi:10.1007/978-3-031-53919-0. ISBN 978-3-031-53918-3.
Suresh, Harini; Guttag, John (November 4, 2021). "A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle". Equity and Access in Algorithms, Mechanisms, and Optimization. EAAMO '21. New York, NY, USA: Association for Computing Machinery. pp. 1–9. doi:10.1145/3465416.3483305. ISBN 978-1-4503-8553-4. S2CID 235436386.
Krištofík, Andrej (April 28, 2025). "Bias in AI (Supported) Decision Making: Old Problems, New Technologies". International Journal for Court Administration. 16 (1) 3. doi:10.36745/ijca.598. ISSN 2156-7964.
Mehrabi, N.; Morstatter, F.; Saxena, N.; Lerman, K.; Galstyan, A. (2021). "A survey on bias and fairness in machine learning". ACM Computing Surveys. 54 (6): 1–35. arXiv:1908.09635. doi:10.1145/3457607. Retrieved April 30, 2025.
Kitchin, Rob (February 25, 2016). "Thinking critically about and researching algorithms" (PDF). Information, Communication & Society. 20 (1): 14–29. doi:10.1080/1369118X.2016.1154087. S2CID 13798875.
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Friedman, Batya; Nissenbaum, Helen (July 1996). "Bias in Computer Systems" (PDF). ACM Transactions on Information Systems. 14 (3): 330–347. doi:10.1145/230538.230561. S2CID 207195759. Retrieved March 10, 2019.
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Goodman, Bryce; Flaxman, Seth (2017). "EU regulations on algorithmic decision-making and a "right to explanation"". AI Magazine. 38 (3): 50. arXiv:1606.08813. doi:10.1609/aimag.v38i3.2741. S2CID 7373959.
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nvlpubs.nist.gov

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shirky.com (Global: low place; English: low place)

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slate.com (Global: 259^th place; English: 188^th place)

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songdata.ca (Global: low place; English: low place)

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springer.com (Global: 274^th place; English: 309^th place)

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ssrn.com (Global: 703^rd place; English: 501^st place)

papers.ssrn.com

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Algorithmic bias (English Wikipedia)

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fortune.com (Global: 433^rd place; English: 284^th place)

georgetown.edu (Global: 2,318^th place; English: 1,652^nd place)

github.com (Global: 383^rd place; English: 320^th place)

google.com (Global: 163^rd place; English: 185^th place)

googleusercontent.com (Global: 243^rd place; English: 882^nd place)

handle.net (Global: 102^nd place; English: 76^th place)

harvard.edu (Global: 18^th place; English: 17^th place)

harvardlawreview.org (Global: low place; English: 6,995^th place)

hbr.org (Global: 2,754^th place; English: 1,686^th place)

hrw.org (Global: 729^th place; English: 650^th place)

ibm.com (Global: 1,131^st place; English: 850^th place)

ieee.org (Global: 652^nd place; English: 515^th place)

informationweek.com (Global: 4,522^nd place; English: 2,903^rd place)

insurancejournal.com (Global: low place; English: 7,621^st place)

jhu.edu (Global: 699^th place; English: 479^th place)

medium.com (Global: 551^st place; English: 406^th place)

mic.com (Global: 4,141^st place; English: 2,523^rd place)

microsoft.com (Global: 153^rd place; English: 151^st place)

mit.edu (Global: 415^th place; English: 327^th place)

nber.org (Global: 2,969^th place; English: 1,994^th place)

nbn-resolving.de (Global: 3,251^st place; English: 7,630^th place)

newyorker.com (Global: 146^th place; English: 110^th place)

nih.gov (Global: 4^th place; English: 4^th place)

nist.gov (Global: 355^th place; English: 454^th place)

nottingham.ac.uk (Global: 4,422^nd place; English: 2,579^th place)

nyc.gov (Global: 1,074^th place; English: 681^st place)

nytimes.com (Global: 7^th place; English: 7^th place)

osf.io (Global: 7,153^rd place; English: 4,975^th place)

propublica.org (Global: 3,281^st place; English: 1,880^th place)

psu.edu (Global: 207^th place; English: 136^th place)

qz.com (Global: 1,110^th place; English: 695^th place)

reuters.com (Global: 49^th place; English: 47^th place)

sagepub.com (Global: 731^st place; English: 638^th place)

sciencedirect.com (Global: 149^th place; English: 178^th place)

seattletimes.com (Global: 519^th place; English: 316^th place)

semanticscholar.org (Global: 11^th place; English: 8^th place)

slate.com (Global: 259^th place; English: 188^th place)

springer.com (Global: 274^th place; English: 309^th place)

squarespace.com (Global: 2,953^rd place; English: 1,823^rd place)

ssrn.com (Global: 703^rd place; English: 501^st place)

stanford.edu (Global: 179^th place; English: 183^rd place)

techcrunch.com (Global: 187^th place; English: 146^th place)

technologyreview.com (Global: 1,943^rd place; English: 1,253^rd place)

theatlantic.com (Global: 228^th place; English: 158^th place)

theconversation.com (Global: 928^th place; English: 651^st place)

theguardian.com (Global: 12^th place; English: 11^th place)

theintercept.com (Global: 2,523^rd place; English: 1,574^th place)

theregister.com (Global: 3,700^th place; English: 2,360^th place)

theverge.com (Global: 114^th place; English: 90^th place)

time.com (Global: 61^st place; English: 54^th place)

ualberta.ca (Global: 3,600^th place; English: 2,528^th place)

uchicago.edu (Global: 230^th place; English: 214^th place)

ucl.ac.uk (Global: 1,306^th place; English: 885^th place)

ucm.es (Global: 1,613^th place; English: 3,265^th place)

umich.edu (Global: 459^th place; English: 360^th place)

umn.edu (Global: 1,266^th place; English: 860^th place)

uni-muenchen.de (Global: 3,337^th place; English: 3,444^th place)

usatoday.com (Global: 41^st place; English: 34^th place)

venturebeat.com (Global: 616^th place; English: 430^th place)