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Chicago
Summer Institute in Computational Social Science Partner Site

June 17, 2019 - June 28, 2019 | Chicago

Sponsored by The Russell Sage Foundation & The Alfred P. Sloan Foundation


From Monday, June 17 to Friday, June 28, 2019, the Summer Institute in Computational Social Science is sponsoring a partner site in Chicago. The purpose of SICSS-Chicago is to bring together Chicagoland graduate students and early career researchers in both social science (broadly conceived) and data science (broadly conceived) to learn and collaborate. Content will include live-streamed lectures from the main site at Princeton University as well as local guest speakers who will present on cutting-edge computational social science research. Topics covered include text analysis, digital data collection, experimental design, non-probability sampling, agent based modeling, and ethics.

Participants will get hands-on experience using computational methods to test social theories by conducting group projects during the second week. One or more collaborative projects that demonstrate extraordinary promise and interdisciplinarity will receive pilot funding for further development, and all participants will be given support in accessing and utilizing the many data sources freely available for research and analysis.

SICSS-Chicago will be held at Northwestern University’s campus in downtown Chicago. There is no cost to participate, and we will provide breakfast and lunch for all on-site days (see schedule for details). Applicants are invited to apply from everywhere, but we cannot provide travel and lodging in Chicago.

We invite applications from graduate students, postdoctoral researchers, and untenured faculty within 7 years of their Ph.D. SICSS-Chicago is committed to diversity and inclusion in computational social science, and we welcome applicants from groups currently underrepresented in computational social science. About twenty participants will be invited.

Participants with less experience with social science research will be expected to complete additional readings in advance of the Institute, and participants with less experience coding will be expected to complete a set of online learning modules on the R or Python programming language. Students doing this preparatory work will be supported by a teaching assistant who will hold online office hours before the Institute.

Application materials should be received by March 30th, 2019.

We will notify applicants via e-mail in mid-April, and will ask participants to confirm their participation very soon thereafter. Inquiries can be sent to sicss.chicago@gmail.com

SICSS-Chicago is generously supported by the Alfred P. Sloan Foundation and the Russell Sage Foundation, and several generous local sponsors:

Organizers

Kat Albrecht

Kat Albrecht is pursuing a PhD in Sociology at Northwestern University and a JD at the Northwestern Pritzker School of Law. Her research focuses on investigating how the structure of data shapes research conclusions and broader sociological theory. Using machine learning methods, quantitative causal inference, and mapping techniques she primarily builds and analyzes large criminal justice datasets. She is especially concerned with the economics of fear, the working definition of homicide, and the general state of crime data. She received her bachelor’s degree from the University of Minnesota where she first began exploring the junction of computational methods and the social sciences.

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Natalie Gallagher

Natalie Gallagher is doctoral student in psychology at Northwestern University. She is fascinated by the human ability to think about social phenomena that emerge from human interaction - social networks and social categories. Exploring these, her work lies at the intersection of social and cognitive research. She draws on psychological, sociological, and computational methods to pursue her questions, and is interested in how research can inform social change. Natalie received her BA in psychology and theater from Georgetown University, and has an MA in psychology from Northwestern.

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Tina Law

Tina Law is a PhD student in sociology at Northwestern. Her research explores why we continue to live in unequal neighborhoods even as our cities are constantly changing. In particular, she uses computational methods and large-scale, digitized data from administrative systems and archival sources to understand how historical events shape contemporary neighborhood racial inequality. She is a National Science Foundation Graduate Research Fellow. She holds an MA in sociology from Yale.

Local Speakers

Joshua Becker

Joshua Becker is a postdoctoral fellow with the Kellogg School of Management and the Northwestern Institute of Complex Systems. Their research on collective intelligence uses agent-based models, online experiments, and data science to examine how network dynamics shape group decisions. Joshua’s current research focuses on how communication networks can increase or decrease the accuracy of factual beliefs in areas such as financial forecasting, political beliefs, and medical diagnoses.

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Sushmita Gopalan

Sushmita is a data scientist at the Northwestern Neighbourhood and Network Initiative at Northwestern University. She uses network and spatial analysis to understand the ways in which social ties, space and their intersection influence behaviour. She has a B.A./M.A. in Economics from the Indian Institute of Technology Madras and an M.A. in Computational Social Science from the University of Chicago.

Maira Khwaja

Maira is a first generation Pakistani-American, born and raised in Pittsburgh. She studied history at the University of Chicago, focusing on the South Side of Chicago. She interviews young people about their experiences with police, produces events and workshops, and guides outreach communications for the Invisible Institute, a 501(c) journalism production company.

Sharon Meraz

Sharon Meraz’s work resides in the interplay of political communication, networked journalism, social networks, and mass media theory. As a scholar centrally interested in political activism and political engagement online, she explores how mass media effect theories take shape and evolve due to the growth of networked, social media technologies that empower political publics. In bringing a social network analytic perspective to the evolving media ecology, she has explored such new theoretical premises as networked gatekeeping, networked framing, network agenda setting, memetics, and virality. Meraz is also interested in automated content analysis, natural language processing, and social network visualization of big data. Her work has explored political activity and activism networks in such social applications as blogs, Twitter, Facebook, and online political forums during electoral cycles, disaster times, and social movements. Meraz is an Associate Professor and Director of Graduate Studies at the University of Illinois at Chicago’s Department of Communication. She also serves on several diversity committees and initiatives at the university, including the Summer Research Opportunities Program (SROP) and Fellowship Committees for Minority Students.

Andrew Papachristos

Andrew Papachristos is Professor of Sociology at Northwestern University and he is the Director of the Northwestern Neighborhood and Network (N3) Initiative. He is also a Faculty Fellow at the Institute for Policy Research at Northwestern. His research aims to understand how the connected nature of cities—how their citizens, neighborhoods, and institutions are tied to one another—affect what we think, feel, and do. His main area of research applies network science to the study of gun violence, police misconduct, illegal gun markets, street gangs, and urban neighborhoods.

Aaron Shaw

Aaron Shaw studies organization, collaboration, governance, and inequality in online environments. His current projects try to understand why and how a few peer production communities (like Wikipedia) grow and sustain valuable public information resources when most do not. Aaron is an Assistant Professor in the Department of Communication Studies at Northwestern University, where he directs the Media, Technology & Society (MTS) Program. He is also a Faculty Associate of the Berkman Klein Center for Internet and Society at Harvard University and a member of the Community Data Science Collective, which he founded together with Benjamin Mako Hill. During 2017-2018, Aaron held a Lenore Annenberg and Wallis Annenberg Fellowship in Communication at the Center for Advanced Study in the Behavioral Sciences (CASBS) at Stanford University.

Rochelle Terman

Rochelle is a Provost’s Postdoctoral Fellow in the Department of Political Science at the University of Chicago, where she’ll begin as Assistant Professor in Fall 2020. Her research examines international norms, gender and advocacy, with a focus on the Muslim world. She is currently working on a book project that examines resistance and defiance towards international norms. The manuscript is based on her dissertation, which won the 2017 Merze Tate (formerly Helen Dwight Reid) Award for the best dissertation in international relations, law, and politics from the American Political Science Association. She teaches computational social science at both the undergraduate and graduate levels, including Machine Learning for Political Science at Stanford and Introduction to Computational Tools and Techniques at Berkeley. She is a certified instructor with Software Carpentry and Data Carpentry. She received her Ph.D. in Political Science with a designated emphasis in Gender & Women’s Studies at the University of California, Berkeley. Before coming to Chicago, she was a post-doc at the Center for International Security and Cooperation at Stanford University.

Teaching Assistants

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Daniel Trielli

Daniel Trielli​ is a PhD student at the Media, Technology and Society program at Northwestern. He is researching computational journalism and how news reaches the public in our increasingly algorithmically-defined world.

Participants

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Abigail Smith

Abby Smith is a PhD student in the Department of Statistics at Northwestern. She is interested in record linkage and missing data in the context of global health and human rights.

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Andrew Szmurlo

Andrew will matriculate the PhD program in Information Science at Cornell University this fall. He is interested in network analysis, causal inference, online communication and incentives. He also likes: running, ML algorithms, cryptocurrency, and pizza.

Image of Chad Van De Wiele

Chad Van De Wiele

Chad Van De Wiele is a PhD student and NSF-IGERT Fellow in the Department of Communication at the University of Illinois at Chicago. Chad employs a variety of methodological and theoretical approaches to study social networks; specifically, his research focuses on political discourse, affect, visuality, and representations and reproductions of race, class, gender, and sexuality within networked spaces. Chad has presented his work at various academic conferences, including NCA, ICA, and AoIR, and has published work in proceedings of the International Joint Conference on Pervasive and Ubiquitous Computing and Social Media + Society.

Image of Christina Schoenberg

Christina Schoenberg

Christina Schonberg is a postdoctoral research associate at UW-Madison. They earned their PhD in Developmental Psychology from UCLA and BA in Psychology from Northwestern University. Christina studies how variability in early language experiences (e.g., infants who are raised in monolingual vs. bilingual homes) influences outcomes such as cognitive flexibility and vocabulary development. Their graduate training focused on behavioral lab-based methods such as eye-tracking, and they are now learning methods for incorporating larger-scale datasets (such as longitudinal speech corpora) into their work as well.

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Crystal Shi

Crystal Shi is a PhD candidate in the School of Hospitality & Tourism Management at Purdue University. She received her Master’s in Hospitality & Tourism Management in December 2013 from Purdue University. Prior to returning to Purdue to pursue her PhD, Crystal spent four years working in the hotel industry. She started as a management trainee at the Fairmont Olympic Hotel in Seattle After that, she was promoted to the position of Food & Beverage Manager at the Fairmont Peace Hotel in Shanghai. Crystal’s research area is primarily employee well-being, turnover intention, and psychological contract in the hotel industry. She is particular interested in conducting research regarding the daily fluctuation of hotel employees’ daily well-being and turnover intention.

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Donghyun Kang

Donghyun Kang is a Ph.D. student in Chicago Sociology Department, working at Knowledge Lab. His overarching academic interest centers on the hybridization of ideas. Using cutting-edge network and text analysis methods, he aspires to shed light on the social conditions, processes, and consequences of interdisciplinary research. He is also interested in employing experimental designs to study the social processes that generate consensus or dissonance when conflicting theories and evidence coexist. Prior to coming to the University of Chicago, Donghyun received a B.A. in Business Administration and M.A. in Sociology at Seoul National University. He also worked as a research associate at Social Network Computing Center (SNCC) in Seoul National University, where he collaborated with researchers from Cyram Inc.

Image of Eric Dunford

Eric Dunford

Eric Dunford is an Associate Director and Assistant Teaching Professor for the Master of Science in Data Science for Public Policy program in the McCourt School of Public Policy at Georgetown University. His research focuses on the organizational and tactical behavior of violent non-state organizations. He is currently involved in a number of projects regarding event data integration, predicting conflict processes, and leveraging online video game data to study how groups innovate and adapt.

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Erin Anderson

Erin M. Anderson is a PhD candidate in Psychology at Northwestern University. Her research examines our learning processes from infancy into adulthood. Currently, she is investigating what helps us recognize patterns across different contexts, and whether being surprised at an unmet expectation can motivate us to seek out more information and revise our beliefs.

Image of Ikiltezilani Mazehuani

Ikiltezilani Mazehuani

Ikiltezi is a graduate student at The University of Chicago where she studies sociology. She has also held public policy and political science fellowships at Princeton and Duke Universities. As an immigration scholar, her research currently explores the effects of legality on immigrants. Specifically, she studies the effects that the Deferred Action for Childhood Arrivals (DACA) program has had on the lives of young people who hold this work authorization, particularly their level of economic integration. Prior to graduate school, Ikiltezi worked for five years on behalf of unaccompanied migrant children through the Office of Refugee Resettlement and Heartland Alliance. She currently works at The University of Chicago’s School of Social Service Administration where she studies the impact that waiting (to regularize one’s citizenship status) has on the lives of older undocumented adults.

Image of JungHwan Yang

JungHwan Yang

JungHwan Yang is an Assistant Professor in the Department of Communication at the University of Illinois at Urbana-Champaign. My research sits at the intersection of media effects, political communication, and political behavior. I study how the current media landscape affects the patterns of news media use of the public and political elites: from understanding people’s reactions to different political events on social media to examine the way some government uses their powers to influence the way people talk about politics. I am currently working on multi-wave panel survey data combined with online tracking data of the panels to understand the political effects of information use.

Image of Kevin Pedraza

Kevin Pedraza

Kevin Pedraza is a PhD candidate in Sociology at Northwestern University. His research interests generally revolve around using geospatial methods to study crime. He hopes to expand his in computational social science skills to develop more sophisticated research designs for understanding variations of crime at the meso-level unit of analysis.

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Leah Castleberry

Leah Castleberry is a first year Master of Public Policy (MPP) candidate at the University of Chicago’s Harris School of Public Policy. Through her studies, she is exploring the ways in which the intersections of business, policy and innovative technologies can be used to create a more equitable future for marginalized communities. Her research interests include cultural competency in artificial intelligence, algorithmic bias and the digital divide. Prior to graduate school, Leah worked as a Senior Cognitive Consultant at IBM Global Business Services. She received a B.B.A. in International Business from Howard University in 2015.

Image of Nick Hagar

Nick Hagar

Nick Hagar is a first-year PhD student at Northwestern University, where he’s a member of the Computational Journalism Lab. He researches the people and technologies that produce journalism online and how they impact each other. He holds a bachelor’s degree in journalism from Northwestern University and has worked in audience development and analytics for several digital newsrooms.

Ole Hexel

Ole Hexel is a doctoral candidate in the joint Ph.D. program between Northwestern University and Sciences Po Paris. At Northwestern, I have worked with Prof. Lincoln Quillian on an international meta-analysis of racial discrimination in hiring. At Sciences Po, I participate in a field experiment on anti-discrimination training. I use Python, mostly for web scraping, and R, for exploring and visualizing data.

Image of Peter Choi

Peter Choi

Eungang (Peter) Choi is a graduate student in the Department of Sociology at The Ohio State University. He is also a graduate affiliate for Institute for Population Research (IPR). His research focuses on identifying fertility trends and using verbal autopsies to analyze causes of death. Methodological interests include Network analysis and NLP. He is originally from Seoul, South Korea.

Image of Rebecca Abbott

Rebecca Abbott

Rebecca Abbot is a PhD candidate in the Sociology department of the University of Illinois at Chicago. Rebecca’s areas of research are primarily focused on economic policy, inequality, racial attitudes and group violence. Rebecca’s dissertation works on improving models forecasting mass atrocities using random forests, clustering and neural networks.

Image of Richard Shafranek

Richard Shafranek

Richard Shafranek is a Ph.D. candidate in the Department of Political Science at Northwestern University. His research, which has appeared in Political Behavior, Political Communication, Political Psychology, and Weather, Climate, and Society, focuses on partisanship and polarization in American politics. Prior to graduate school, he worked as a market researcher, a political campaign operative, and in the non-profit sector, and was a Fulbright scholar to Indonesia (2011-12). He received a B.A. in Political Science from Allegheny College in 2010.

Image of Subhayan Mukerjee

Subhayan Mukerjee

Subhayan Mukerjee is a doctoral candidate at the Annenberg School for Communication of the University of Pennsylvania, where he researches political communication with a focus on online audiences and online political polarization. In his dissertation, he is studying the structure of online audience networks in India, and theorizing the manner in which audiences navigate cultural divides in India’s uniquely multi-cultural society. His general interest in using computational techniques to answer questions of substantive social import stems from his early childhood fascination with Isaac Asimov’s Foundation series and the fictitious science of psychohistory. In his spare time, he can either be found cooking or supporting Arsenal football club with an aching in his heart.

Image of Tomoko Okada

Tomoko Okada

Tomoko Okada is a PhD candidate in the Department of Life Sciences Communication at the University of Wisconsin-Madison. Her areas of research interest lie in the intersection of science communication and political communication. She is especially interested in rural-urban divides in values about science and emerging technologies and unequal access to scientific news. In her dissertation, she explores these issues by combining survey data, text data of newspapers, and Twitter data.

Image of Zixi Chen

Zixi Chen

Zixi Chen is a PhD candidate from the Measurement and Quantitative Methods program of College of Education of Michigan State University. Her research interests include social network analysis, hierarchical linear model, and sensitivity analysis in social science. She is a quantitative research member of the Teachers in Social Media project, where she gains extensive experience of using traditional and exploratory/computational statistical methods for educational research. In this project, she particularly interests in learning teachers’ resource acquisition behaviors in social medias for their students learning.

Pre-arrival

As we discussed in our call for applications, we have arranged two types of training prior to the event this summer. Some students have more sophisticated coding skills but little exposure to social science; other students have significant exposure to social science but lack strong coding skills.

Coding

The majority of the coding work presented at the 2019 SICSS will employ R. However, you are welcome to employ a language of your choice, such as Python, Julia, or other languages that are commonly used by computational social scientists. If you would like to work in R, we recommend that you complete the free RStudio Primers, which can be supplemented by the open access book R for Data Science by Garrett Grolemund and Hadley Wickham. RStudio Primers cover 6 topics: The Basics, Working with Data, Visualize Data, Tidy Your Data, Iterate, and Write Functions. If you already feel comfortable with these topics (either in R or some other language), then you do not need to complete these Primers.

If you would like more practice after completing the RStudio Primers, some other materials that we can recommend are:

Reading List

Our institute will bring together people from many fields, and therefore we think that asking you to do some reading before you arrive will help us use our time together more effectively. First, we ask you to read Matt’s book, Bit by Bit: Social Research in the Digital Age, which is a broad introduction to computational social science. Parts of this book will be review for most of you, but if we all read this book ahead of time, then we can use our time together for more advanced topics.

Also, for students with little or no exposure to sociology, economics, or political science, we have assembled a collection of exemplary papers in the core areas addressed by the Russell Sage Foundation. Neither your work nor the work we develop together at the institute need map neatly onto these categories, but if those with less exposure to social science read these, we will increase the chances of interdisciplinary cross-pollination, which we view as critical to the future of computational social science.

Future of Work

Behavioral Economics

Race, Ethnicity, and Immigration

Social Inequality

Schedule and materials

Monday June 17, 2019 - Introduction and Ethics

  • 8:00 AM - 8:15 AM: Logistics (No Live Stream)

  • 8:15 AM - 8:30 AM: Introductions (No Live Stream)

  • 8:30 AM - 9:00 AM: Introduction to Computational Social Science Slides (Princeton Live Stream)

  • 9:00 AM - 9:30 AM: Why SICSS? Slides (Princeton Live Stream)

  • 9:30 AM - 9:45 AM: Coffee Break (No Live Stream)

  • 9:45 AM - 10:30 AM: Ethics: Principles-Based Approach Slides (Princeton Live Stream)

  • 10:30 AM - 11:15 AM: Four Areas of Difficulty Slides (Princeton Live Stream)

  • 11:15 AM - 11:30 AM: Introduction to Group Exercise Slides (Princeton Live Stream)

  • 11:30 AM - 12:30 PM: Guest Speaker: Aaron Shaw Link to video (Chicago Live Stream)

  • 12:30 PM - 1:30 PM: Lunch (No Live Stream)

  • 1:30 PM - 2:45 PM: Group Exercise Case study 1 Case study 2 (No Live Stream)

  • 2:45 PM - 3:00 PM: Break (No Live Stream)

  • 3:00 PM - 4:30 PM: Guest Speaker: Alondra Nelson (Princeton Live Stream)

Tuesday June 18, 2019 - Collecting Digital Trace Data

  • 8:00 AM - 8:15 AM: Logistics (No Live Stream)

  • 8:15 AM - 8:30 AM: What is Digital Trace Data? Slides (Princeton Live Stream)

  • 8:30 AM - 8:45 AM: Strengths and Weaknesses of Digital Trace Data Slides, Annotated Code (Princeton Live Stream)

  • 8:45 AM - 9:15 AM: Screen-Scraping Slides, Annotated Code (Princeton Live Stream)

  • 9:15 AM - 9:30 AM: Coffee Break (No Live Stream)

  • 9:30 AM - 10:00 AM: APIs Slides, Annotated Code (Princeton Live Stream)

  • 10:00 AM - 11:30 AM: Building Apps & Bots Slides, Annotated Code (Princeton Live Stream)

  • 11:30 AM - 12:30 PM: Guest Speaker: Sharon Meraz Link to video (Chicago Live Stream)

  • 12:30 PM - 1:30 PM: Lunch (No Live Stream)

  • 1:30 PM - 3:00 PM: Group Exercise (No Live Stream)

  • 3:00 PM - 4:30 PM: Guest Speaker: Beth Noveck (Princeton Live Stream)

Wednesday June 19, 2019 - Automated Text Analysis

  • 8:00 AM - 8:15 AM: Logistics (No Live Stream)

  • 8:15 AM - 8:30 AM: History of Quantitative Text Analysis Slides (Princeton Live Stream)

  • 8:30 AM - 8:45 AM: Basic Text Analysis/GREP Slides, Annotated Code (Princeton Live Stream)

  • 8:45 AM - 9:00 AM: Dictionary-Based Text Analysis Slides, Annotated Code (Princeton Live Stream)

  • 9:00 AM - 9:15 AM: Coffee Break (No Live Stream)

  • 9:15 AM - 10:15 AM: Topic Models/Structural Topic Models Slides from Chris, Annotated Code from Chris (Princeton Live Stream)

  • 10:15 AM - 10:20 AM: Break (No Live Stream)

  • 10:20 AM - 11:30 AM: Text Networks Slides, Annotated Code (Princeton Live Stream)

  • 11:30 AM - 12:30 PM: Lunch and Guest Speaker: Jennifer Pan (Princeton Live Stream)

  • 12:30 PM - 3:00 PM: Group Exercise (No Live Stream)

  • 3:00 PM - 4:00 PM: Chicago Guest Speaker: Maira Khwaja Link to video (Chicago Live Stream)

Thursday June 20, 2019 - Surveys in the Digital Age

  • 8:00 AM - 8:15 AM: Logistics (No Live Stream)

  • 8:15 AM - 8:35 AM: Survey research in the digital age Slides (Princeton Live Stream)

  • 8:35 AM - 8:55 AM: Probability and non-probability sampling Slides (Princeton Live Stream)

  • 8:55 AM - 9:15 AM: Computer-administered interviews and wiki surveys Slides (Princeton Live Stream)

  • 9:15 AM - 9:35 AM: Combining surveys and big data Slides (Princeton Live Stream)

  • 9:35 AM - 9:45 AM: Coffee Break (No Live Stream)

  • 9:45 AM - 10:15 AM: Group exercise introduction Slides (Princeton Live Stream)

  • 10:15 AM - 11:30 AM: Begin Group Exercise (No Live Stream)

  • 11:30 AM - 12:30 PM: Chicago Guest Speaker Rochelle Terman Slides Link to video (Chicago Live Stream)

  • 12:30 PM - 1:30 PM: Lunch (No Live Stream)

  • 1:30 PM - 2:15 PM: Continue Group Exercise (No Live Stream)

  • 2:15 PM - 2:45 PM: Discuss activity and open-source data Slides (Princeton Live Stream)

  • 2:45 PM - 3:00 PM: Break (No Live Stream)

  • 3:00 PM - 4:30 PM: Guest Speaker: Justin Grimmer (Princeton Live Stream)

Friday June 21, 2019 - Modeling & Experiments

  • 8:00 AM - 8:30 AM: Logistics (No Live Stream)

  • 8:30 AM - 11:30 AM: Modeling & Experiments w/ Josh Becker Slides (No Live Stream)

  • 11:30 AM - 12:30 PM: Lunch (No Live Stream)

  • 12:30 PM - 1:30 PM: Group Formation for Second Week (No Live Stream)

  • 1:30 PM - 2:30 PM: Andy Papachristos talk Link to video (Chicago Live Stream)

  • 2:30 PM - 3:30 PM: Group Formation for Second Week (No Live Stream)

  • 3:30 PM - 4:30 PM: Guest Speaker: Annie Liang (Princeton Live Stream)

Saturday June 22, 2019 - Day off

Sunday June 23, 2019 - Day off

Monday June 24, 2019 - Work on group projects

Tuesday June 25, 2019 - Work on group projects

Wednesday June 26, 2019 - Work on group projects

  • 11:30 AM - 12:30 PM: Panel: Navigating the Computational Social Science Job Market

Thursday June 27, 2019 - Work on group projects

Friday June 28, 2019 - Present group projects

  • 9:00 AM - 10:00 AM: Machine Learning Talk (Optional)

  • 12:30 PM - 1:30 PM: Lunch and flash talks (No Live Stream)

  • 1:30 - 4:30 PM: Present group projects (Not open to public/ No livestream)