This weekly workshop highlights the work of those pioneering data science analytical techniques and social science and computation methods while bringing together graduate students, post-docs, and faculty all working at the nexus of computation and big, social science questions. The workshop also allows regular participants to share works in progress for feedback, fosters robust dialogue between young scholars in these emerging fields, and showcases local scholars leading pedagogical seminars on new papers or methods.

The 2021-2022 Computational Social Science Workshop meets in-person and virtually each Thursday from 11:00 am to 12:20 pm. The presentation will be held at 1155 East 60th St (room will vary by week). MACSS students who have a last name starting with A through L (Group 1) are required to attend this week’s presentation in-person. The rest of MACSS students (Group 2) and all other attendees will need to join the meeting via Zoom. Students in Group 2 are expected to show up in-person next week. Join Zoom Meeting | Meeting ID: 959 8172 8771 | Passcode: 525749

You can join our official listserv here. Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the first issues page of the workshop’s public repository.

Autumn 2021

October 21: What We Teach About Race and Gender: Representation in Images and Text of Children's Books

Anjali Adukia, Assistant Professor at the University of Chicago Harris School of Public Policy and the College

This week’s suggested readings: Adukia, Anjali and Eble, Alex and Harrison, Emileigh and Runesha, Hakizumwami Birali and Szasz, Teodora, ‘What We Teach About Race and Gender: Representation in Images and Text of Children’s Books.’ Working Paper.

Attendance: The talk will be held in Rm 142 of 1155 East 60th St. MACSS students who have a last name starting with M through Z (Group 2) are required to attend this week’s talk in person. All MACSS faculty members are also welcome to join the talk in person. The rest of MACSS students (Group 1) and all other attendees will need to join the meeting via Zoom (link).

Participation: Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the issues page of the workshop’s public repository.


October 14: Algorithmic Behavioral Science: Automated Discovery of Human Biases

Sendhil Mullainathan, Roman Family University Professor of Computation and Behavioral Science at Chicago Booth. 

This week’s suggested reading: Kleinberg, Jon, Jens Ludwig, Sendhil Mullainathan, and Ziad Obermeyer. 2015. ‘Prediction Policy Problems.’ American Economic Review, 105 (5): 491-95.


October 7: Tapping into Talent: Coupling Education and Innovation Policies for Economic Growth

Ufuk Akcigit, Arnold C. Harberger Professor of Economics; Senior Research Fellow, Brookings Institute; Research Associate, National Bureau of Economic Research, Center for Economic Policy Research, and the Center for Economic Studies;  and a Distinguished Research Fellow, Koc University.

This week’s suggested readings: Ufuk Akcigit, Jeremy G. Pearce, and Marta Prato. 2021. ‘Tapping into Talent: Coupling Education and Innovation Policies for Economic Growth.’ Working Paper.


September 30: Social Computing & Computational Social Science 

James Evans, Professor in the Department of Sociology, Director of Knowledge Lab, and Co-Director for the Masters in Computational Social Science Program

This week’s recommended reading: James Evans. 2020. ‘Social Computing Unhinged.’ Journal of Social Computing, 1: 1.


Spring 2021

May 27: The Many Markets Impacted By Left-Digit Bias

Devin Pope, Professor of Behavioral Science and Economics, Booth School of Business, University of Chicago

Registration: The presentation will be held virtually on Zoom. For security purposes, please register through this link to request access. Only accounts affiliated with the University of Chicago will be granted access.

This week’s recommended reading: Lacetera, N., Pope, D. G., & Sydnor, J. R. (2012). Heuristic thinking and limited attention in the car market. American Economic Review, 102(5), 2206-36.


May 20: ‘Understanding’ and Prediction: Controlled Examinations of Meaning Sensitivity in Pre-Trained NLP Models

Alluson Ettinger, Assistant Professor, Department of Linguistics, University of Chicago

This week’s required reading: Ettinger, A. (2020). What BERT is not: Lessons from a new suite of psycholinguistic diagnostics for language models. Transactions of the Association for Computational Linguistics, 8, 34-48. This week’s additional suggested reading (in order of priority): Yu, L., & Ettinger, A. (2020). Assessing Phrasal Representation and Composition in Transformers. arXiv preprint arXiv:2010.03763 and Ettinger, A., Elgohary, A., Phillips, C., Resnik, P. (2018). Assessing Composition in Sentence Vector Representations. Proceedings of the 27th International Conference on Computational Linguistics.

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May 13: Developing Robot Teammates That Enhance Social Dynamics in Human-Robot Teams

Sarah Sebo, Assistant Professor, Department of Computer Science, University of Chicago

This week’s recommended reading: Strohkorb Sebo, S., Dong, L. L., Chang, N., & Scassellati, B. (2020, March). Strategies for the inclusion of human members within human-robot teams. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (pp. 309-317) and Sebo, S., Dong, L. L., Chang, N., Lewkowicz, M., Schutzman, M., & Scassellati, B. (2020). The Influence of Robot Verbal Support on Human Team Members: Encouraging Outgroup Contributions and Suppressing Ingroup Supportive Behavior. Frontiers in Psychology, 11, 3584.


May 6: Psychological Profiling in the Digital Environment: Risks and Opportunities

Michal Kosinski, Associate Professor, Organizational Behavior, Stanford University Graduate School of Business

This week’s recommended reading: Kosinski, M. (2021). Facial recognition technology can expose political orientation from naturalistic facial images. Scientific Reports, 11(1), 1-7 and Youyou, W., Kosinski, M., & Stillwell, D. (2015). Computer-based personality judgments are more accurate than those made by humans. Proceedings of the National Academy of Sciences, 112(4), 1036-1040.


April 29: How to Trust a Machine?

Iyad Rahwan, Director, Center for Humans and Machines, Max Planck Institute for Human Development

This week’s recommended reading: E. Awad, S. Dsouza, R. Kim, J. Schulz, J. Henrich, A. Shariff, J.-F. Bonnefon, I. Rahwan (2018). The Moral Machine experiment. Nature. 562 (7729)E. Awad, S. Dsouza, J.-F. Bonnefon, A. Shariff, I. Rahwan (2020). Crowdsourcing Moral Machines. Communications of the ACM, March 2020, Vol. 63 No. 3, Pages 48-55; and I. Rahwan, et al (2019). Machine Behaviour. Nature. 68, pages 477–486.


April 22: Network Structure And Diversity In The Eco-Evolutionary Assembly Of Host-Pathogen Systems

Mercedes Pascual, Professor in the Department of Ecology and Evolution at the University of Chicago, and an external faculty of the Santa Fe Institute

This week’s required reading: He, Q., Pilosof, S., Tiedje, K.E., Ruybal-Pesántez, S., Artzy-Randrup, Y., Baskerville, E. B., … & Pascual, M. (2018). Networks of genetic similarity reveal non-neutral processes shape strain structure in Plasmodium falciparum. Nature Communications, 9(1817), 1-12. Additional suggestion for reading: Pilosof, S., Alcalá-Corona, S. A., Wang, T., Kim, T., Maslov, S., Whitaker, R., & Pascual, M. (2020). The network structure and eco-evolutionary dynamics of CRISPR-induced immune diversification. Nature Ecology & Evolution, 4(12), 1650-1660.

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April 15: Accelerating Science with Human Versus Alien Artificial Intelligence

James Evans, Director of the Knowledge Lab; Founder/Faculty Chair of the Computational Social Science Program; Professor of Sociology, University of Chicago 

Recommended reading: Sourati, J., Evans, J. (2021). Accelerating science with human versus alien artificial intelligences.


April 8: Efficient Experimental Design With Adaptive Experimentation

Eytan Bakshy, Facebook Core Data Science Team, Facebook

Recommended reading: Letham, B., Feng, Q., Daulton, S., Bakshy, E. (2021). Real-World Bayesian Optimization with A/B Tests. Additional suggestions for optional reading: Letham, B., Karrer, B., Ottoni, G., Bakshy, E. (2019). Constrained Bayesian Optimization with Noisy Experiments. Bayesian Analysis, 14(2), (pp. 495-519); and Bakshy, E., Dworkin, L., Karrer, B., Kashin, K., Letham, B., Murthy, A., Singh, S. (2018). AE: A domain-agnostic platform for adaptive experimentation. In ‘Workshop on System for ML.’


April 1: Diversity and Inequality in Social Networks: From Recommendation to Information Diffusion

Ana-Andrea Stoica, PhD Candidate, Columbia University

Suggested readings: Stoica, A.A., Han, J.X., Chaintreau, A. (2020). Seeding Network Influence in Biased Networks and the Benefits of Diversity. Proceedings of The Web Conference 2020, (pp. 2089-2098) and Stoica, A.A., Riederer, C., Chaintreau, A. (2018). Algorithmic Glass Ceiling in Social Networks: The effects of social recommendations on network diversity. Proceedings of the 2018 World Wide Web Conference (pp. 923-932).


Winter 2021

March 4: Mis- and Disinformation Dynamics in Critical Conversations

Renee Diresta, Research Manager, Stanford Internet Observatory

This week’s suggested readings: Executive Summary of The Long Fuse: Misinformation and the 2020 Election (Center for an Informed Public, Digital Forensic Research Lab, Graphika, & Stanford Internet Observatory, 2021); Additional related reading: Center for an Informed Public, Digital Forensic Research Lab, Graphika, & Stanford Internet Observatory (2021). The Long Fuse: Misinformation and the 2020 Election. Stanford Digital Repository: Election Integrity Partnership. v2.0.0


February 25: (In)citing Action to Realize an Equitable Future

Danielle Bassett, J. Peter Skirkanich Professor, University of Pennsylvania, Departments of Bioengineering, Electrical & Systems Engineering, Physics & Astronomy, Neurology, and Psychiatry

Suggested readings: Dworkin, J. D., Linn, K. A., Teich, E. G., Zurn, P., Shinohara, R. T., & Bassett, D. S. (2020). The extent and drivers of gender imbalance in neuroscience reference lists. Nature neuroscience, 23(8), 918-926. and Bertolero, M. A., Dworkin, J. D., David, S. U., Lloreda, C. L., Srivastava, P., Stiso, J., … & Bassett, D. S. (2020 Preprint). Racial and ethnic imbalance in neuroscience reference lists and intersections with gender. BioRxiv. Additional readings: Dworkin, J., Zurn, P., & Bassett, D. S. (2020). (In) citing action to realize an equitable future. Neuron, 106(6), 890-894.


February 18: Resilience to Online Censorship

Margaret (Molly) Roberts, Associate Professor of Political Science, University of California San Diego

Suggested readings: Chang, K. C., Hobbs, W. R., Roberts, M. & Steinert-Threlkeld, Z.(2020). Crisis is a Gateway to Censored Information: The Case of Coronavirus in China. 21st Century China Center Research Paper Series, Paper No. 2021-01. Available at SSRN: and Pan, J., & Roberts, M. E. (2020). Censorship’s Effect on Incidental Exposure to Information: Evidence From Wikipedia. SAGE Open, 10(1), 2158244019894068 and Hobbs, W. R., & Roberts, M. E. (2018). How sudden censorship can increase access to information. American Political Science Review, 112(3), 621-636.


February 11: Online Rumors, Misinformation and Disinformation: The Perfect Storm of COVID-19

Kate Starbird, Associate Professor, Department of Human Centered Design & Engineering, University of Washington

This week’s suggested readings: Methodology: Maddock, J., Starbird, K., Al-Hassani, H. J., Sandoval, D. E., Orand, M., & Mason, R. M. (2015, February). Characterizing online rumoring behavior using multi-dimensional signatures. In Proceedings of the 18th ACM conference on computer supported cooperative work & social computing (pp. 228-241) and Content: Starbird, K., Spiro, E., & West, J. (2020, May 9) This Covid-19 Misinformation Went Viral. Here’s What We Learned. The Washington Post. 


February 4: Chinese Online Discussion Around Democracy in the 2010s

Yinxian Zhang, Assistant Professor of Sociology, CUNY Queens College. 

Suggested reading is a working paper that has been distributed to the MACSS listserv and is available by request from Sanja Miklin ().


January 28: #HashtagActivism: Networks of Race and Gender Justice

Brooke Foucault Welles, Associate Professor, Department of Communication Studies, Northeastern University

Suggested readings: 1) Jackson, S. J., & Foucault Welles, B. (2015). Hijacking# myNYPD: Social media dissent and networked counterpublics. Journal of Communication, 65(6), 932-952.; 2) Gallagher, R. J., Stowell, E., Parker, A. G., & Foucault Welles, B. (2019). Reclaiming stigmatized narratives: The networked disclosure landscape of# MeToo. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1-30.; and 3) additional reading: Jackson, S. J., Bailey, M., & Welles, B. F. (2020). # HashtagActivism: Networks of Race and Gender Justice. MIT Press.


January 21: The Curse of Abundance: Understanding and Managing Personal Effects in the Digital Age

Chris Kanich, Associate Professor, Department of Computer Science, University of Illinois at Chicago

Suggested readings: Khan, M. T., Hyun, M., Kanich, C., & Ur, B. (2018, April). Forgotten but not gone: Identifying the need for longitudinal data management in cloud storage. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1-12). A draft of a paper that has been distributed to the MACSS listserv and is available by request from Sanja Miklin (


January 14: Artificial Intelligence for Social Good: When Machines Learn Human-Like Biases from Data

Aylin Caliskan, Assistant Professor of Computer Science, School of Engineering & Applied Science, George Washington University

Suggested readings: Caliskan, A., Bryson, J. J., & Narayanan, A. (2017). Semantics derived automatically from language corpora contain human-like biases. Science, 356(6334), 183-186 and Steed, R. & Caliskan, A. (2021). Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases. ACM FAccT; Additional readings: Guo, W. & Caliskan, A. (2020). Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases and Toney, A. & Caliskan, A. (2020). ValNorm: A New Word Embedding Intrinsic Evaluation Method Reveals Valence Biases are Consistent Across Languages and Over Decades.


Autumn 2020

November 19: Pandemic Policymaking

Philip Waggoner, Assistant Instructional Professor in the Masters in the Computational Social Science program and a Political Scientist

Suggested readings: Waggoner, 2020. ‘Pandemic Policymaking: Learning the Lower Dimensional Manifold of Congressional Responsiveness’ and Waggoner, 2020. ‘A Computational Exploration of the Evolution of Governmental Policy Responses to Epidemics Before and During the Era of COIVD-19’


November 12: Clustering Countries-Improving Measurement in Comparative Political Research

Brooke Luetgert, Computational Scientist - SSD Research & Computing Center; Lecturer in Digital Studies, University of Chicago

Suggested readings: Luetgert, 2020. ‘Clustering Countries-Improving Measurement in Comparative Political Research’


November 5: Children as a Solution to Explore Exploitations

Alison Gopnik, Professor of Psychology, University of California at Berkeley

Suggested readings: Gopnik 2020. ‘Childhood as a solution to explore-exploit tensions’ Phil. Trans. R. Soc, B 375: 20190502


October 29: Why We Don't Click: Interrogating the Relationship Between Viewing and Clicking in Social Media Contexts by Exploring the 'Non-Click'

Nicole B. Ellison, Karl E. Weick Collegiate Professor of Information in the School of Information, University of Michigan

Suggested readings: Ellison, Trieu, Schoenebeck, Brewer, & Israni 2020. ‘Why We Don’t Click: Interrogating the Relationship Between Viewing and Clicking in Social Media Contexts by Exploring the ’Non-Click’’

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October 22: Experimentation and Incrementalism: The Impact of the Adoption of A/B Testing

Berk Can Deniz, Doctoral Student, Stanford Graduate School of Business, Macro Organizational Behavior Goup, Stanford University

Suggested readings: Berk Can Deniz 2020. ‘Experimentation and Incrementalism: The Impact of the Adoption of A/B Testing’


October 15: Rethinking Depression in Cities: Evidence and Theory for Lower Rates in Larger Urban Areas

Andrew J. Stier, Doctoral Student in the Integrative Neuroscience Program, University of Chicago.

Marc G. Berman, Associate Professor, Department of Psychology; Co-Director, Masters in Computational Social Science Program; and Director of the Environmental Neuroscience Lab.

Suggested readings: Andrew J. Stier et al. 2020. ‘Rethinking Depression in Cities: Evidence and Theory for Lower Rates in Larger Urban Areas.’


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October 8 - The Inka Writing System: An Exploration of Khipu Sign Conventions (Recording)

Jon Clindaniel, Assistant Instructional Professor in Computational Social Science, University of Chicago

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October 1 - Fall Welcome Mixer 

The Computational Social Science Workshop at the University of Chicago cordially invites you to attend this week’s event. We welcome the new class of MACSS students, greet our returning second year's, and invite all faculty and guests to mingle with our students, discuss big ideas, and celebrate the first Computation Workshop of the academic year.


Spring 2020

May 28 - Social Bootstrapping of Economic Value

Lynette Shaw, Assistant Professor of Complex Systems, Post-Doctoral Scholar, Michigan Society of Fellows, University of Michigan

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May 21 - Gender Stereotypes Reflected in the Distributional Structure of 25 Languages

Molly Lewis, Research Scientist - Psychology and Social Decision Sciences Departments, Carnegie Mellon University


May 14 - Protecting Privacy in a World Filled with Smart Devices

Heather Zheng, Neubauer Professor of Computer Science, University of Chicago


May 7 - The Structure of U.S. College Networks on Facebook

Bogdan State, Data Scientist Facebook


April 30 - Human-in-the-Loop Machine Learning

Robert Munro, Author, "Human-in-the-Loop Machine Learning" 


April 9 - Drawings of Real-World Scenes during Free Recall Reveal Detailed Object and Spatial Information in Memory

Wilma Bainbridge, Assistant Professor, Department of Psychology, University of Chicago

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Winter 2020

March 6 - How Exploitation and Exploration Shape the Knowledge Space

Hyejin Youn, Assistant Professor of Management & Organizations, Northwestern University - Kellogg School of Management


February 27 - Modeling Context-Dependent Latent Effect Heterogeneity with Applications to Study Public Political Polarization

Diogo Ferrari, Assistant Instructional Professor in Computational Social Science, University of Chicago

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February 6 - School, Studying, And Smarts: The Gender of Education Across 80 Years of American Print Media, 1930-2009

Andrei BoutylineAssistant Professor, Department of Sociology, University of Michigan

Andrei Boutyline

January 30th - Network Structures of Collective Intelligence: The Contingent Benefits of Group Discussion

Joshua BeckerPostdoctoral Fellow, Kellogg School of Management, Northwestern Institute on Complex Systems, Northwestern University

Joshua Becker

January 23rd - Toward a Science of Failure

Dashun Wang, Associate Professor of Management and Organizations - Kellogg School of Management, Northwestern University

Dashun Wang

January 16th - Designing For Trust: A Behavioral Framework For Sharing Economy Platforms

Paolo Parigi  - Lead Trust Scientist - Airbnb

Natã Barbosa - Phd Candidate - University of Illinois at Urbana-Champaign, School of Information Sciences

Paolo Parigi

Natã Barbosa

January 9th - Network Science or Applied Graph Theory? Examining the Network of Indirect Collaboration in a Department of Mathematics

Moses Boudourides, Visiting Professor of Mathematics - New York University Abu Dhabi; Faculty - Northwestern University School of Professional Studies Data Science Program

Moses Boudourides

Autumn 2019

October 3rd - Fall Welcome Mixer

Join us as we welcome the new class of MACSS students, greet our returning second years, and invite all faculty and guests to mingle with our students, discuss big ideas, celebrate the first Computation Workshop of the academic year in our new room, and propose speakers, topics, and organizations for the workshop.

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October 10th - Big Data in Medicine: A panel of distinguished University of Chicago faculty

Chaired by Jeremy Greene, a renowned historian of medicine (John Hopkins School of Medicine)

Jeremy Greene

October 17th - Science and Technology Advance through Surprise

James Evans, Professor of Sociology, Director of the Knowledge Lab, Faculty Director of the Masters Program in Computational Social Science, and External Professor at the Santa Fe Institute, University of Chicago

James Evans

October 24th - Machine Politics: A Roundtable

Fred Turner, Professor of Communication (Stanford University), Adrian Johns, Professor of History (UChicago) & Joel Isaac, Professor of Social Thought (UChicago)

Fred Turner

October 31st - Calling Bullshit: Data Reasoning in a Digital World

Jevin West, Associate Professor - Information School, University of Washington & Carl Bergstrom, Professor of Computational Biology and Behavior, University of Washington

Jevin West

Carl Bergstrom

November 7th - How to Measure Legislative District Compactness If You only Know it When You See it

Gary King, the Albert J. Weatherhead III University Professor at Harvard University

Gary King

November 14th - Islamophobia and Media Portrayals of Muslim Women: A Computational Text Analysis of US News Coverage

Rochelle Terman, Provost’s Postdoctoral Fellow in Political Science, University of Chicago

Rochelle Terman