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From Sunday, June 17 to Friday, June 29, 2018, the Summer Institute in Computational Social Science is sponsoring a Chicago partner site hosted at Northwestern University. The purpose of the Summer Institute is to bring together graduate students and early career researchers in both social science (broadly conceived) and data science (broadly conceived). Content will include live-streamed lectures from the main site at Duke University as well as guest speakers who will present on cutting-edge computational research and methods. Topics covered include text analysis, digital data collection, experimental design, non-probability sampling, agent based modeling, and ethics.
One of the main goals of SICSS is to bring together scholars from a range of computational and social sciences to share their complementary skillsets and enhance each others work. Participants will get hands-on experience using computational methods to test social theories and will develop group projects to present at the end of 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.
Participation is restricted to graduate students, postdoctoral researchers, and untenured faculty within 7 years of their Ph.D. Due to limited space, up to 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. To facilitate the planning process, you must submit your application materials by April 21st, 2018.
There is no cost to participate in SICSS-Chicago, and we will provide breakfast and lunch for all on-site days (see schedule for details). Participants from any geographic location are encouraged to apply, and those traveling from outside the Chicago area must provide their own travel and lodging.
SICSS-Chicago is generously supported by the Alfred P. Sloan Foundation and the Russell Sage Foundation, and several generous local sponsors:
Kat Albrecht is pursuing a PhD in Sociology at Northwestern University. 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.
Joshua Becker defended his PhD at the University of Pennsylvania and will be starting as a postdoctoral fellow with the Kellogg School of Management and the Northwestern Institute of Complex Systems. His research on collective intelligence uses formal models and experimental tests to examine how social network structure shapes group decisions. His current research focuses on how communication networks can be harnessed to tap the wisdom of crowds and improve estimation accuracy on tasks such as financial forecasting, political beliefs, and medical diagnoses.
Jeremy Foote is a PhD candidate in the Media, Technology, and Society program at Northwestern. He is a member of the Community Data Science Collective. Using computational social science tools like social network analysis and simulation, he researches how people cooperate to create online collective goods, focusing particularly on how new projects get started and which ones grow.
Matt Salganik, Chris Bail, Deen Freelon, David Lazer, Kristian Lum, Sendhil Mullainathan, Cynthia Rudin, and Duncan Watts.
Ned Smith is an Associate Professor of Management and Organizations at the Kellogg School of Management, Associate Professor (by courtesy) of Sociology, core faculty member of the Northwestern Institute for Complexity (NICO), and faculty associate at the Northwestern Institute for Policy Research.
Sheena is an assistant professor in the College of Computing and Digital Media at DePaul University in Chicago, IL. Sheena co-directs the Technology for Social Good | Research and Design Lab with Dr. Denise Nacu.
Ágnes Horvát is an Assistant Professor in the Department of Communication Studies, an affiliated faculty of the Northwestern Institute on Complex Systems (NICO), and the Department of Management and Organizations of the Kellogg School of Management (by courtesy).
Alex is the Program Director and a Lecturer for the M.S. in Computational Analysis and Public Policy degree at the University of Chicago. In addition to teaching courses on Data Visualization and Large Scale Data Methods for policy research, he is a contributing Data Scientist at the Urban Institute.
Rayid Ghani is the Director of the Center for Data Science & Public Policy and a Senior Fellow at the University of Chicago Harris School of Public Policy and the Computation Institute.
Diego Gómez-Zará is a Ph.D. Student in the Technology and Social Behavior program at Northwestern University. He is a graduate research assistant of the SONIC Lab. He researches how team assembly is supported by technologies, diffusion of information through social media, and social network analysis.
Anna McKean is a joint PhD student in Management & Organizations and Sociology. Her research interests include social movements, organizational change and influence, and non-market strategy. Currently, her research focuses on how corporations respond to, participate in, and influence social and political activism and policy change.
Basak is a Postdoctoral Fellow at Northwestern University. She received her Ph.D. in Political Science from the University of Pennsylvania in 2016. Her research centers on collective action and conflict. Much of her work is set in the context of regimes, contentious politics, and international economy, where she combines computational methods, network analysis, and qualitative methods. Basak’s co-authored chapter, When Does Repression Trigger Mass Protest?, was acknowledged by Cornell University with the 2015 Sidney Tarrow Best Article Prize for a paper written by a graduate student in the field of contentious politics or in European politics, sociology or history.
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.
Dustin Stoltz is a PhD candidate in sociology at the University of Notre Dame and a Doctoral Affiliate with the Kellogg Institute for International Studies. He researches the production, distribution, consumption, and consequences of ideas, specifically ideas about the economy. As part of his dissertation, he applies network analysis and text analysis to a unique dataset of management consultants working in North America and Southeast Asia and the numerous articles they write.
Libby Trudeau earned her MA from the University of Chicago and is currently working on a PhD in sociology at the University of Notre Dame. Her research focusses on cultural meaning-making particularly around the social construction of gender and sexuality. Her current projects focus on discourses regarding sex work and human trafficking in the U.S. She is excited about using mixed- methods techniques to gain creative insights.
Hanlin Li is a Ph.D. student in the Technology and Social Behavior program at Northwestern University. She is a member of the People, Space, and Algorithms Research Group. She studies how individuals and organizations use technology to support social causes. Taking mixed methods approaches, she designs, builds, and tests civic technologies that empower collective action online.
Hee Youn Kwon received her PhD in Systems and Entrepreneurial Engineering at the University of Illinois at Urbana-Champaign in May 2018. At the University of Illinois, she had worked as a research and teaching assistant in the Department of Industrial and Enterprise Systems Engineering (ISE), the Computational Science and Engineering Program (CSE), and the Department of Computer Science (CS). She wrote her PhD dissertation on new developments in causal inference using Balance Optimization Subset Selection under supervision of Professor Sheldon H. Jacobson. Prior to Illinois, she received a B.S. in Mathematical Sciences from Korea Advanced Institute of Science and Technology (KAIST) and an M.Phil. in Economics from University of Oxford.
Igor Zakhlebin is pursuing a PhD in Technology and Social Behavior, a joint program in Computer Science and Communications at Northwestern University. His current projects study how crowds of people come together to produce new cultural works and how they collectively pay attention to them. To answer these questions, Igor performs large-scale data analyses and builds computational tools to support them. His methods of choice are network analysis, machine learning, and computational modeling.
Iva Terwilliger is a PhD student in the Health Sciences Integrated PhD Program (HSIP) with a concentration in Healthcare Quality and Patient Safety. She studies teamwork in healthcare and is part of Nick Soulakis’ lab. Iva is interested in using mixed methods to better understand how teamwork can be better utilized to improve the quality of patient care. Before coming to Northwestern, Iva worked as an RN at the VA and NYU Langone.
Jeremiah Bohr is currently an Assistant Professor of Sociology at the University of Wisconsin Oshkosh, and received his Ph.D. from the University of Illinois at Urbana-Champaign. His research focuses on climate change denial (both in terms of organization and individual attitudes), household energy use and energy insecurity, and text analysis. He is currently using computational methods to study the communication of climate change by politicians on social media.
Josey VanOrsdale is currently a doctoral student at the University of Nebraska-Lincoln in the sociology department. Her research interests are in biosociology, minority health disparities, and quantitative and computational methods. Her most recent research has encapsulated these interests by looking at the subbaccalaureate education level within the education-health gradient. For the past year, she has also worked as part of the LifeHD lab at the University of Nebraska. She has recently joined and looks forward to contributing to the Research, Evaluation, & Analysis for Community Health (REACH) lab.
Kyosuke Tanaka is a Ph.D. student in the Media, Technology, and Society program at Northwestern University. He is interested in network perception and cognition. His recent research explores how people decode, recall and learn the social networks around them.
Roland Adorjani is a Ph.D. Candidate in the School of Sociology at University College Dublin. My dissertation focuses on large-scale discourse analysis of e-therapy conversations. His project is also linked to collaborations with enterprise partners in the mental e-health domain. Other research interests include large-scale social media discourse analysis of Twitter hashtag campaigns and science of science. Prior to graduate school, he worked as a data scientist at opening.io.
Sarah Otner is a Research Fellow in the Strategy & Organizational Behavior group at Imperial College Business School (London, UK). Her research uses economic sociology and social psychology in order to understand the mechanisms and the consequences of social status. Sarah’s research focuses on prestige and expertise, and especially award competitions; her current research projects examine prize scarcity, prize sharing, establishing new prizes, and prize refusals.
Mohamad Hosseinioun is pursuing a Ph.D. in Management Information Systems at the University of Illinois at Chicago. He has received his bachelor’s and master’s degrees in Industrial and Systems Engineering and his research focuses on Causal Inference and Prediction in Complex and Dynamic Systems. Using Statistical and Fuzzy Machine Learning methods, Network Analysis, and Econometrics he investigates the behavior of social and economic entities. He is especially interested in collective realities and collective decision making, where the outcome of the “whole” is significantly altered by the interconnected behavior of the “individual”s.
Shu Fu is a third-year PhD at the Department of Political Science at the University of Chicago. He studies American politics and political methodology. His research interests include American presidency, election, and public opinion. He is also interested in machine learning and causal inference in methods. He is currently working on multiple research projects. One project is related to the presidential partisan particularism, explaining how and why American presidents impact distributive politics and allocate disproportionately more federal funds toward their core states. Another project is to use advanced textual analysis to understand how first ladies communicate with the public. His dissertation is on American presidential public appeals and party building.
Yian Yin is currently a PhD candidate of Industrial Engineering & Management Sciences (IEMS) at McCormick School of Engineering and Applied Sciences, Northwestern University. He is also affiliated to Social Complexity group at Northwestern Institute on Complex Systems (NICO). His current research lies in the boundary of data mining, complex systems and computational social science, with a focus on understanding successes and failures in individual career from large-scale datasets. He received his bachelor’s degrees in Statistics and Economics from Peking University in 2016.
Yini Zhang is a Ph.D. candidate in the School of Journalism and Mass Communication at the University of Wisconsin Madison. She studies how emergent communication technologies impact the dynamics and outcomes of political communication. Her research mainly concerns agency, algorithms, and attention in the hybrid media system. She is also interested in media psychology such as hostile media and fact-check effects in the new media environment. She does mixed method research by applying both traditional communication research methods, such as survey and experiment, and computational methods, such as social network clustering and topic modeling, to mining insights about individual communication and media system in an ever evolving media landscape.
Yixue Wang is a Ph.D. student in Technology and Social Behavior program at Northwestern University, a joint program between the Department of Electrical Engineering and Computer Science and the Department of Communication Studies. Her research interests are in computational social science, computational journalism, and data science for social good. She is particularly interested in how social networks, media exposure, and geospatial environment influence propagation, reinforcement, or polarization of ideas and attitudes using network analysis, machine learning and geospatial analysis. She is a member of Data Science fellow at Northwestern Data Science Initiative.
In order to prepare for SICSS-Chicago, we ask that you follow the same pre-arrival syllabus as the other SICSS locations. We are grateful to Matt Salganik and Chris Bail for preparing this reading list and the recommended Datacamp courses. In addition to the R courses posted on the main SICSS site, we have included a list of recommended Python courses.
As we discussed in our call for applications, SICSS has 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.
The majority of the coding work presented at the 2018 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 following courses within DataCamp, a website that teaches people how to code. Obviously, you only need to complete the classes with material that you would like to learn.
If you cannot afford datacamp, check out Chris Bail’s Intro to R slides at http://www.chrisbail.net/p/learn-comp-soc.html
The 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.
1:00-5:00 Welcome Reception and Research Speed Dating (Local Guest Speaker Rayid Ghani) (Room 2110)
8:30-9:00 Breakfast [On Livestream: Introduction to computational social science] slides
9:00-9:30 Why SICSS? slides
9:30-9:45 Coffee Break
9:45-10:30 Ethics: Principles-based approach (Livestream) slides
10:30-11:15 Four areas of difficulty (Livestream) slides
11:15-12:15 Guest Speaker: Alex Engler (Local)
3:00-4:30 Guest Speaker: Duncan Watts (Livestream)
9:00-9:15 What is digital trace data? slides
11:00-12:00 Guest Speaker: Sheena Erete (Local)
11:30-3:00 Lunch and Group Exercise description of exercise
3:00-4:30 Guest Speaker: Jim Wilson (Livestream)
4:30-5:30 Group Excercise Continued
8:00-4:30 Parallel with Main Site (Livestream) [Local guest speaker Ned Smith @ 3:00pm]
8:00-4:30 Parallel with Main Site (Livestream)
9:15-9:30 Why Experiments?
9:30-9:45 Generating theories using formal models
9:45-10:00 Web experiments using free and open source platforms
10:00-10:15 Coffee break
10:15-11:00 Moving beyind simple experiments (2017 Livestream Video)
11:00-11:30 Four strategies for experiments (2017 Livestream Video)
11:30-12:00 Introduction to Emprica.ly
12:00-12:15 Introduction to Ground Truth / Red Team Challenge
12:15-12:30 Introduction to Fragile Families Challenge
12:30-3:30 Fragile Families Challenge
3:30-5:00 Plan group projects
9am-10am Work on Projects
10:00-11:00 Guest Speaker
11:00-1:00 Lunch and Finish Projects
1:00-4:30 Present Projects
4:30-7:30 Closing Reception