From the evening of Sunday, June 16 to the morning of Saturday, June 29, 2019, the Russell Sage Foundation and the Alfred P. Sloan Foundation will sponsor a partner site in Boston for the Summer Institute in Computational Social Science. The purpose of the Summer Institute is to bring together graduate students, postdoctoral researchers, and beginning faculty interested in computational social science. The Summer Institute is for both social scientists (broadly conceived) and data scientists (broadly conceived).
The site is organized by former participants of the 2018 SICSS workshop and will feature live streams of the primary location at Princeton in addition to local speakers. In the afternoons of the first week, participants at the Boston location will also be able to work in teams to learn how to implement the material from the lecture. In the second week, participants will join teams to develop a research project related to computational social science.
There will be ample opportunities for students to discuss their ideas and research with the organizers, other participants, and visiting speakers. One goal of this partner location is to build and expand the network of computational social scientists in the Boston area.
We are inviting applications from Ph.D. students, postdoctoral researchers, and untenured faculty within 7 years of their Ph.D. Meals will be provided during the workshop and we expect to invite about twenty participants. 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 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 were due on Friday, April 12, 2019. We can no longer accept new applications. There is no cost to participating in the Boston workshop.
All events will be held at:
50 Ames Street
Cambridge, MA 02142
We are grateful to the Russell Sage Foundation and the Alfred P. Sloan Foundation for their sponsorship of the partner site. We also thank MIT’s IDSS for providing the space and the Questrom School of Business at Boston University for additional funding. We look forward to announcing additional sponsors for this partner location in the coming months.
Ryan J. Gallagher is a PhD student at Northeastern University. At the Network Science Institute, he researches the dynamics of social networks using tools and theory from natural language processing and communications. He currently studies the affective phenomena of networked counterpublics. Ryan holds an MS in mathematics from the University of Vermont, where he worked with the Computational Story Lab at the Vermont Complex Systems Center, and a BA in math from the University of Connecticut.
David is a Fellow at the Kennedy School of Government at Harvard University. He received his PhD from the Department of Social and Decision Sciences at Carnegie Mellon University. His research looks at the desire to avoid information that may be painful to learn yet improve decision-making, persuasion on politically charged topics, and behavioral policy interventions (nudges).
Eaman Jahani is a graduate research assistant pursuing a PhD degree in Social and Engineering Systems with a minor in Statistics at MIT IDSS. Prior to MIT, he was a software engineer at Google for 4 years. His main training is in statistics and computer science, but recently he has been appreciating econometrics and modeling in applied economics. His past research examined the extent of bubbles vs truth-seeking in cryptocurrency markets and socio-economic prediction in social networks. His current research focuses on structural factors such as networks or institutions that regenerate inequality at a micro scale. Eaman spends too much time reading political commentaries.
Yan is currently pursuing a Ph.D. at Human Dynamics group at MIT. She received dual masters in Computer Science and Transportation Engineering from MIT in 2016. Yan is interested in using a broad range of computational techniques to understand the network effect of social influence. In particular, she works on the inference, identification, and modeling of social influence and social learning with large-scale behavioral data in a networked environment. Besides, she also works on the combining network structure and personal attributes in maximizing cascading payoff.
Sanaz Mobasseri is an Assistant Professor of Organizational Behavior at Boston University’s Questrom School of Business. She received her PhD from the Management of Organizations Department at UC Berkeley’s Haas School of Business. Her research examines the role of emotion, cognition, and culture in shaping social networks and labor market outcomes. Much of her work is situated in organizational settings, where she examine the microfoundations of workplace inequality. Although grounded in sociology and organizational theory, her work integrates theoretical insights from social psychology and sociolinguistics. Her research methods are similarly diverse, ranging from experimental studies in the lab to audit studies in the field to computational approaches applied to large archival data sets.
I am an economist who studies digitization and search and matching markets. I’ve written papers on topics such as the design of Airbnb’s search and matching algorithm, reputation systems, online job search, and 401(k) contribution choices by workers. I am currently an assistant professor of marketing at the Boston University Questrom School of Business. My research has been published in both economics journals (American Economic Review, The Review of Economics and Statistics) and computer science conferences (ACM-EC). I’ve provided expert input about the digital economy at the President’s Council on Science and Technology and the Federal Trade Commission. Prior to BU, I was a postdoc at the Initiative on the Digital Economy at MIT. I worked as a data scientist at Airbnb while completing a Ph.D. in Economics at Stanford University. In my free time, I climb, write, and make a podcast.
I am a computational social scientist in the Management of Organizations group at the Haas School of Business at UC Berkeley. My current research interests are around structure, governance, and inequality in sociotechnical systems; measurement and social networks; and the social structure of the opioid epidemic. I am currently a postdoc with Toby Stuart and Mathijs de Vaan at the Haas School of Business at UC Berkeley, where I am also a member of the Algorithmic Fairness and Opacity Working Group. I hold a PhD in Computer Science, which focused on computational tools for understanding social networks, advised by Aaron Clauset at the University of Colorado Boulder. During my PhD I was fortunate to spend time at Microsoft Research NYC, mentored by Duncan Watts (intern 2015, 2016 & consulting researcher, 2015-2017), and to have funding from an NSF Graduate Research Fellowship. In 2015, I served as an organizer for the Women in Machine Learning Workshop, a technical workshop co-located with NIPS, and as of 2018 I am on the Board of Directors for Women in Machine Learning. I previously received a BA in Mathematical Methods in the Social Sciences and Mathematics from Northwestern University.
In Song Kim is an Associate Professor of Political Science. He holds a Ph.D. in Politics from Princeton University, where he received a Harold W. Dodds Fellowship for 2012-2013. His dissertation research on the effects of firms’ lobbying on trade policy-making received the 2015 Mancur Olson Award for the Best Dissertation in Political Economy. Professor Kim works at the intersection of statistical machine learning and political science. His research explores trade policies of various countries in the world on highly specific products, and political activities of firms that produce and trade goods internationally. He is also interested in developing statistical methods for causal inference with panel data, and text analysis for analyzing political documents.
Jacqueline Ng Lane is a Postdoctoral Fellow at Harvard Business School at the Laboratory for Innovation Science at Harvard (LISH). Her research integrates insights from organizational theory, technology adoption, team effectiveness, and social networks to better understand how companies can implement new technologies to more effectively collaborate, share knowledge and improve organizational outcomes. A second avenue of her research examines people’s socio-technical motivations for forming, maintain, and dissolving collaborative ties with others, particularly when organizing into interdisciplinary or diverse teams. She holds a PhD in Management Sciences from Northwestern University, where she was a member of the Science of Networks in Communities (SONIC) lab and Northwestern Institute on Complex Systems (NICO). Before her PhD, Jacqueline worked in sales & trading, equity research, and customer relationship management. She earned an executive MBA from Columbia University and a B.S.E in Operations Research & Financial Engineering from Princeton University.
Laura K. Nelson is a sociologist who uses computational methods to study social movements, culture, gender, institutions, and the history of feminism. Using computer-assisted texts analysis and network analysis, her dissertation examined the political logics underlying women’s movements in New York City and Chicago from 1865-1975. She is interested in further developing automated text analysis methods and best-practices for sociology and digital humanities. She received her Ph.D. in sociology from the University of California, Berkeley. In 2014-2016 she was a postdoc in Management and Organizations in the Kellogg School of Management at Northwestern University, and is on leave this year as a fellow for Digital Humanities @ Berkeley and the Berkeley Institute for Data Science at the University of California, Berkeley.
Brooke Foucault Welles is an Associate Professor in the department of Communication Studies and core faculty of the Network Science Institute at Northeastern University. Combining the methods of network science with theories from the social sciences, Foucault Welles studies how online communication networks enable and constrain behavior, with particular emphasis on how these networks facilitate the pursuit of individual, team, and collective goals. Much of her work is interdisciplinary and collaborative, with co-authors from computer science, political science, digital humanities, design, and public health. Her recent contributions include a series of studies of the transformative power of networked counterpublics, techniques for the longitudinal analysis of communication networks using event-based network analysis, and guidelines for the effective use of network visualizations in scientific and lay publications. Her work is funded by grants from the US Army Research Office and US Army Research Lab, and has been featured in leading social science journals such as the Journal of Communication, Information, Communication and Society, and The Annals of the American Academy of Political and Social Science. She serves on the editorial board of the journal Web Science and was part of the team that developed the Network Literacy Essential Concepts and Core Ideas.
Jinhua Zhao is the Edward and Joyce Linde Associate Professor of City and Transportation Planning at the Massachusetts Institute of Technology (MIT). Prof. Zhao brings behavioral science and transportation technology together to shape travel behavior, design mobility system and reform urban policies. He develops methods to sense, predict, nudge and regulate travel behavior; designs multimodal mobility system that integrates autonomous vehicles, shared mobility and public transport; and reform urban policies to govern the new technologies and business models. Prof. Zhao sees transportation as a language to describe a person, to characterize a city, and to understand an institution. Prof. Zhao leads long-term research collaborations with major transportation authorities and operators worldwide including London, Chicago, Hong Kong and Singapore. He holds Master of Science, Master of City Planning and Ph.D. degrees from MIT and a Bachelor’s degree from Tongji University. Prof. Zhao directs the Urban Mobility Lab (mobility.mit.edu) at MIT and is the founder of the MIT Automated Mobility Policy Project.
The schedule will be posted in the coming months.