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 each Thursday from 11:00 am to 12:20 pm. 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.


Spring 2022


May 26: Enhancing the Wisdom of Crowds

Jack Soll, Professor of Management and Organizations at Fuqua School of Business, Duke University

The talk will be held in person in room 295 of 1155 E 60th Street.

This week’s recommended readings:

Please also complete the following survey by 8pm Wednesday before the talk. 

https://dukefuqua.qualtrics.com/jfe/form/SV_cvg1ca6nVS49uQu

May 19: How Information Flows from the World to China

Jennifer Pan, Associate Professor of Communication and, by courtesy, of Political Science and of Sociology, Stanford Univeristy

The talk will be held in person in room 295 of 1155 E 60th Street.

This week’s recommended readings:

May 05: Deplatforming Right-Wing Extremistis on Twitter Following the January 6th Insurrection

David Lazer, University Distinguished Professor of Political Science and Computer Science, Northeastern University

The talk will be held in person in room 295 of 1155 E 60th Street.

This week’s recommended readings:

April 28: Unbiased AI in a Biased World: Mission (IM) Possible?

Sandra Wachter, Associate Professor, Senior Research Fellow at Oxford Internet Institute, University of Oxford 

The talk will be held virtually on Zoom. Please join via Zoom at the link provided: (link).

This week’s recommended readings:

April 21: Out of Scope, Out of Mind: Expanding Frontiers for Fair ML in Social Decision Making

Serena Wang, PhD Student in Computer Science at University of California, Berkeley   

The talk will be held in room 295 in 1155 E 60th Street.

This week’s recommended readings:

April 14: What Do We Mean By 'Non - Discriminatory' In Statistical Prediction Tasks?

Nathan Srebro, Professor at the Toyota Technical Institute at Chicago,with cross- appointments at the University of Chicago's Department of Computer Science, and Committee on Computational and Applied Mathmatics  

The talk will be held in room 295 in 1155 E 60th Street.

This week’s recommended readings:

April 7: Deep Learning for Individual Heterogeneity: An Automatic Inference Framework

Max Farrell, Associate Professor of Econometrics and Statistics, University of Chicago Booth School of Business

The talk will be held in room 295 in 1155 E 60th Street.

This week’s recommended readings:

March 31: The Social and Biographical Locus of Innovation

James Evans, Director, Knowledge Lab; Max Palevsky Professor, Sociology, University of Chicago; Fellow, Computation Institute; Co-Director, Masters in Computational Social Science Program

The talk will be held in room 295 in 1155 E 60th Street.

This week’s recommended readings:

 


Winter 2022


March 10: A Computational Theory of Socially-Embedded Decision Making

Alex 'Sandy' Pentland, Professor of Media Arts and Sciences, MIT

The talk will be held virtually on Zoom at the link provided: (link).

This week’s recommended readings:

 

March 3: Agent_Zero and Generative Social Science

Joshua Epstein, Professor of Epidemiology, New York University

The talk will be held both in-person and virtually on Zoom. Students can come in-person to room 295 of 1155 East 60th St or watch virtually by joining via Zoom at the link provided: (link).

This week’s readings include excerpts from a single book. The suggested reading is the Preface, first 20 pages of Part 1, and first 20 pages of Part 2. The Preface, Part 1, and Part 2 have been split into separate documents for your convenience:

Preface: - Epstein, J. M. (2014). Agent_Zero. Princeton University Press.

Part 1 (first 20 pgs recommended): - Epstein, J. M. (2014). Agent_Zero. Princeton University Press.

Part 2 (first 20 pgs recommended): - Epstein, J. M. (2014). Agent_Zero. Princeton University Press.

February 24: Polarized Brains on Polarizing Media: Divergent Neural and Semantic Representations of Political Content

Yuan Chang (YC) Leong, Assistant Professor in the Department of Psychology, UChicago

The talk will be held both in-person and virtually on Zoom. Students can come in-person to room 295 of 1155 East 60th St or watch virtually by joining via Zoom at the link provided: (link).

This week’s reading: Leong, Y. C., Chen, J., Willer, R., & Zaki, J. (2020). Conservative and liberal attitudes drive polarized neural responses to political content. Proceedings of the National Academy of Sciences, 117(44), 27731-27739.

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February 17: The Dynamics of U.S. Business Firms: Data, Theories, and Models

Robert Axtell, Professor of Computational Science at George Mason University; External Faculty Fellow at the Santa Fe Institute; Visiting Scientist at Google Research, and currently Visiting Professor at the Sloan School at MIT

This week’s recommended readings: Axtell, R. (2018). Endogenous firm dynamics and labor flows via heterogeneous agents. In Handbook of computational economics (Vol. 4, pp. 157-213). Elsevier and Axtell, R. (2016). 120 million agents self-organize into 6 million firms: A model of the US private sector. In Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems (pp. 806-816).

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February 10: Sampling from Memory to Guide Decisions

Akram Bakkour, Assistant Professor, Department of Psychology, University of Chicago

This week’s reading: Bakkour, A., Palombo, D. J., Zylberberg, A., Kang, Y. H., Reid, A., Verfaellie, M., … & Shohamy, D. (2019). The hippocampus supports deliberation during value-based decisions. elife, 8, e46080.

Please find the supplemental information online here.

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February 3: Language, Perception, and Causal Inference in Online Communication

Zhao Wang, Assistant Instructional Professor in the MACSS program at the University of Chicago

This week's readings: Wang, Z., & Culotta, A. (2019, July). When Do Words Matter? Understanding the Impact of Lexical Choice on Audience Perception Using Individual Treatment Effect Estimation. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, No. 01, pp. 7233-7240)  and Wang, Z., & Culotta, A. (2020). Robustness to spurious correlations in text classification via automatically generated counterfactuals. arXiv preprint arXiv:2012.10040.

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January 27: Subject Data Access Rights: Measurements of and Targeting Practices and Lessons for Future Transparency Mechanisms

Blase Ur, Neubauer Family Assistant Professor of Computer Science at the University of Chicago

This week's readings: Wei, M., Stamos, M., Veys, S., Reitinger, N., Goodman, J., Herman, M., … & Ur, B. (2020). What Twitter Knows: Characterizing Ad Targeting Practices, User Perceptions, and Ad Explanations Through Users’ Own Twitter Data. In 29th {USENIX} Security Symposium ({USENIX} Security 20) (pp. 145-162).  
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January 20: Reporting from the Frint Lines of Social Media Research: From Quick and Dirty to Ideal

Dr. Sherry Emery, Senior Fellow in Public Health and the Director of the Social Data Collaboratory at NORC at the University of Chicago

This week's readings:    Kim, Y., Emery, S. L., Vera, L., David, B., & Huang, J. (2021). At the speed of Juul: measuring the Twitter conversation related to ENDS and Juul across space and time (2017–2018). Tobacco Control, 30(2), 137-146. and Huang, J., Duan, Z., Kwok, J., Binns, S., Vera, L. E., Kim, Y., … & Emery, S. L. (2019). Vaping versus JUULing: how the extraordinary growth and marketing of JUUL transformed the US retail e-cigarette market. Tobacco Control, 28(2), 146-151.

 
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January 13: The Fractal Brain and Cognitive Effort

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

This week's readings: Stier, A. J., Cardenas-Iniguez, C., Kardan, O. J., Moore, T. M., Meyer, F. A., Rosenberg, M. D., … & Berman, M. G. (2021). A Scale-Free Gradient of Cognitive Resource Disruptions in Childhood Psychopathology. bioRxiv.

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Autumn 2021


December 16: Combating Disinformation on Social Media and its Challenges 

Kai Shu, Gladwin Development Chair Assistant Professor, Department of Computer Science, Illinois Institute of Technology

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December 2: Detection and Description of Change in Visual Streams

Greg Shakhnarovich, Professor, Toyota Technological Institute at Chicago; CS Department, University of Chicago

This week’s suggested readings: David Gilton, Ruotian Luo, Rebbecca Willett, and Greg Shaknarovich. 2020. ‘Detection and Description of Change in Visual Streams.’

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November 18: Only 3 Left at this Price: A Tale of Misleading Online Content and Consumer Protections

Marshini Chetty, Assistant Professor, Department of Computer Science; Director, Amyoli Internet Research Laboratory (AIR Lab), University of Chicago 

This week’s required reading: Schaffner, B., Lingareddy, N., & Chetty, M. Understanding Account Deletion and Related Dark Patterns on Social Media. Working Paper; and optional reading: Mathur, A., Acar, G., Friedman, M. J., Lucherini, E., Mayer, J., Chetty, M., & Narayanan, A. (2019). Dark patterns at scale: Findings from a crawl of 11K shopping websites. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1-32.

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November 11: Integrating Interactive Devices with the User's Body

Pedro Lopes, Assistant Professor in Computer Science, University of Chicago

This week’s required readings: Kasahara, S., Nishida, J., & Lopes, P. (2019, May). Preemptive Action: Accelerating Human Reaction Using Electrical Muscle Stimulation Without Compromising Agency. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-15)Brooks, J., Nagles, S., & Lopes, P. (2020, April). Trigeminal-based Temperature Illusions. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-12); and Mueller, F. F., Lopes, P., Strohmeier, P., Ju, W., Seim, C., Weigel, M., … & Maes, P. (2020, April). Next steps for human-computer integration. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-15).

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October 28: In Search of Synergy in the Task Space using High-Throughput Experiment Design

Abdullah Almaatouq, Douglas Drane Career Professor; Assistant Professor - Sloan School of Management, and Affiliated Faculty at the Center for Computational Engineering and Connection Science Research Initiative, Massachusetts Institute of Technology

This week’s required readings: Almaatouq, A., Griffiths, T.L., Suchow, J.W., Whiting, M.E., Evans, J., & Watts, D.J., ‘Playing 20,0000 Questions with Nature: High-Throughput Experimentation in Social and Behavioral Science’ and Almaatouq, A., Alsobay, M., Yin, M., & Watts, D. J. (2021). ‘Task complexity moderates group synergy.’ Proceedings of the National Academy of Sciences, 118(36).

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.’

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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).

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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

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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.

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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: https://ssrn.com/abstract=3756577 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.

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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. 

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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 ().

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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.

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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 (smiklin@uchicago.edu).

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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.

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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’

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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’

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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

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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’

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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.

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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

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

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

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

Bogdan State, Data Scientist Facebook

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

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

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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

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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