RTI International (RTI) is proud to host and be a partner institution of the Summer Institute in Computation Social Science (SICSS) from the morning of Monday, June 17 to evening of Friday, June 28. Sessions and lectures will take place in tandem with the main event at Princeton University, along with 9 other partner institutions around the world.
RTI will be the only non-university to host a partner site for SICSS. RTI is an independent, nonprofit research institute centrally located between Duke University, the University of North Carolina at Chapel Hill, and North Carolina State University.
The purpose of the Summer Institute is to bring together graduate students, postdoctoral researchers, and beginning faculty interested in computational social science. It is for both social and data scientists, broadly conceived.
The instructional program will involve lectures, group problem sets, and participant-led research projects. Topics will include:
In the afternoons of the first week, participants will work in teams to learn how to implement the material from the morning lectures. In the second week, participants will join teams to develop a research project related to computational social science. RTI will also feature live streams of speakers at Princeton University and other locations in addition to local speakers at RTI during the two weeks. There will be ample opportunities for students to discuss their ideas and research with the organizers, other participants, and visiting speakers. All materials created by faculty and students for the Summer Institute will be released open source.
All events will be held at:
Ph.D. students, postdoctoral researchers, and untenured faculty within 7 years of their Ph.D.
If you are interested in attending the Summer Institute in Research Triangle Park, NC, please complete the steps listed on the application page. The application deadline is Friday, April 12, 2019.
There is no cost to participate in the Summer Institute. Breakfast and lunch vouchers will be provided. Participants are responsible for their own travel and accommodations.
For questions please email us at email@example.com.
The Summer Institute in Computational Social Science is funded in part by grants from the Russell Sage Foundation and the Alfred P. Sloan Foundation.
Antje Kirchner, PhD, is a Research Survey Methodologist at RTI International and an Adjunct Research Assistant Professor at the University of Nebraska - Lincoln. Her research addresses challenges in survey methodology, including ways to examine nonresponse bias using machine learning techniques, adaptive/responsive designs, assessing the quality of survey and administrative data, and how to improve response quality in surveys using behavior coding and paradata. Her research has been published in journals such as Public Opinion Quarterly, Journal of Survey Statistics and Methodology, and Journal of the American Statistical Association. She recently organized the “Big Data Meets Survey Science (BigSurv18)” conference.
Craig A. Hill, PhD, is the Senior Vice President for Survey, Computing, and Statistical Sciences division. He creates the strategy and vision for his business unit, and manages and directs a portfolio of more than 150 studies and more than 500 professional staff. Dr. Hill received his PhD in quantitative methods from the Political Science department at the University of New Orleans and has published in a variety of journals. He also was the lead editor for Social Media, Sociality, and Survey Research (Wiley, 2013). Recent presentations include “Thoughts, Ruminations, and Twitter-ready Soundbites on Data Science, Big Data, and Social Science Research” (2017 Royal Statistical Society) and “Moving Social Science into the Fourth Paradigm” at BigSurv18 in Barcelona.
Alan Blatecky, PhD, is a Visiting Fellow at RTI International and has broad expertise in high performance computing, international networking, computational science, Artificial Intelligence and advanced cyberinfrastructure. As a Visiting Fellow, Alan focuses on integrating and deploying advanced technologies to transform research and education. Alan previously was the Director for the Office of Cyberinfrastructure (OCI) at the National Science Foundation, Deputy Director of the Renaissance Computing Institute, Executive Director of Research and Programs at the San Diego Supercomputing Center, and Vice President of Information Technology at MCNC and NCREN (North Carolina Research and Education Network). Alan recently co-authored a book; “Reproduciblity: A Primer on Semantics and Implications for Research.
Helen Jang, Senior Director at RTI International, leads Project Catapult, a company initiative focusing on applying computational social science and directs the Center for Digital Innovation in Education and Workforce Development division. Her work leverages data and emerging technologies to improve policy and practice. Pivotal work includes the National Center for Education Statistics’ DataLab, which offers public access to data from 50 federal studies, USAID’s Early Grade Reading Barometer, which offers a wealth of actionable assessment data to improve literacy outcomes, and the Evaluation Engine, a quasi-experimental impact evaluation tool designed to help states use their longitudinal education data to improve instruction.
Jacqueline Olich, PhD, is an administrator, educator and entrepreneur with experience building partnerships and developing innovative initiatives. She joined RTI International in 2014. As RTI’s first senior director of University Collaborations, she leads RTI International’s University Collaboration Office (UCO), which serves as a catalyst and hub for outreach at the university level. She develops and manages partnerships with leading regional, national and international academic institutions. She leads the RTI University Scholars Program and the RTI Internship Program. Dr. Olich is an adjunct associate professor in the UNC Gillings School of Global Public Health’s Public Health Leadership Program.
Sam Adams is a Senior Artificial Intelligence Researcher at RTI International and also the Mission Architect for Project Catapult, a company initiative focusing on applying computational social science. He applies artificial intelligence and knowledge graph techniques to the unique data curation and integration challenges that data scientists face. He holds 29 patents and previously spent more than 2 decades with IBM Research, where he was appointed one of the first IBM Distinguished Engineers. Mr. Adams played a leading role in various strategic initiatives—including artificial general intelligence, autonomous learning, end-user programming, contextual data fusion, big data and analytics, enterprise-scale data curation, and massive multicore programming and high-performance graph database acceleration; he also applied Internet of Things data and reactive knowledge graphs to the challenges of global elder care.
Emily Hadley is a Data Scientist with the Center for Data Science at RTI International. She uses her technical skills on a variety of health, education, and computational social science projects. Emily has experience with machine learning techniques, natural language processing, predictive analytics, data visualization, and data ethics, as well as expertise programming in Python, R, and SQL. She holds a BS in Statistics with a second major in Public Policy from Duke University and a MS in Analytics from the Institute for Advanced Analytics at North Carolina State University.
Marcus Mann is a sociologist who studies science, politics, knowledge and media using computational methods. His current research uses data from Twitter to examine how political media consumption patterns affect susceptibility to political disinformation. He holds a BA in English from UMass - Amherst and master’s degrees in Religious Studies and Sociology from Duke University. He is currently finishing his PhD and will begin his new job as an Assistant Professor of Sociology at Purdue University this coming fall.
We have arranged two types of training prior to the event this summer: (1) Coding Modules and (2) Suggested Reading. These resources are meant to support both students possessing more sophisticated coding skills but little exposure to social science and students with significant exposure to social science but lack coding skills.
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 following courses within DataCamp, a website with courses on many topics related to data science. Obviously, you only need to complete the classes with material that you would like to learn.
We thank DataCamp for making these materials available to admitted participants though their DataCamp for the Classroom program.
If you would like a different way to learn similar material, we recommend Introduction to R for Social Scientists taught by Charles Lanfear. This course includes video, code, and assignments.
The Summer 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 (Read online or purchase from Amazon, Barnes & Noble, IndieBound, or Princeton University Press), 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.
The schedule will be posted in the coming months.