June 17 – June 28, 2019 | RTI International (RTI)
8:30 - 9:00 Check-in
9:00 - 9:15 Welcome/Logistics
9:15 - 9:30 Introductions
9:30 - 10:00 Introduction to computational social science (Princeton livestream) Slides
10:00 - 10:30 Why SICSS? (Princeton livestream) Slides
10:30 - 10:45 Coffee Break
10:45 - 11:30 Ethics: Principles-based approach (Princeton livestream) Slides
11:30 - 12:15 Four areas of difficulty: informed consent, informational risk, privacy, and making decisions in the face of uncertainty (Princeton livestream) Slides
12:15 - 12:30 Introduction to the group exercise (Princeton livestream) Slides
12:30 - 1:30 Lunch at Horizon as a group
1:30 - 3:45 Group exercise Case study 1 Case study 2
3:45 - 4:00 Break
4:00 - 5:30 Guest speaker: Alondra Nelson (Princeton livestream)
9:00 - 9:15 Logistics
9:15 - 9:30 What is digital trace data? Slides
9:30 - 9:45 Strengths and weakness of digital trace data Slides, Annotated Code
9:45 - 10:15 Screen-Scraping Slides, Annotated Code
10:15 - 10:30 Coffee Break
10:30 - 11:00 Application Programming Interfaces Slides, Annotated Code
11:00 - 12:30 Building Apps and Bots for Social Science Research Slides, Annotated Code
12:30 - 1:30 Lunch
1:30 - 3:45 Group Exercise
3:45 - 4:00 Break
4:00 - 5:30 Guest speaker: Beth Noveck (Princeton livestream)
9:00 - 9:15 Logistics
9:15 - 9:30 History of quantitative text analysis Slides
9:30 - 9:45 Basic Text Analysis/GREP Slides, Annotated Code
9:45 - 10:00 Dictionary-Based Text Analysis Slides, Annotated Code
10:00 - 10:15 Coffee Break
10:15 - 11:15 Topic models/Structural Topic Models (Guest Lecture by Brandon Stewart Slides from Brandon Slides from Chris, Annotated Code from Chris
11:15 - 11:20 Break
11:20 - 12:30 Text Networks Slides, Annotated Code
12:30 - 2:00 Lunch and Guest Speaker: Jennifer Pan
2:00 - 4:00 Group Exercise
4:00 - 5:30 Guest speaker: Sam Adams Livestream
5:30 - 7:30 NC BBQ Cookout Social
9:00 - 9:15 Logistics (Not open to public/No livestream)
9:15 - 9:35 Survey research in the digital age Slides
9:35 - 9:55 Probability and non-probability sampling Slides
9:55 - 10:15 Computer-administered interviews and wiki surveys Slides
10:15 - 10:35 Combining surveys and big data Slides
10:35 - 10:45 Coffee break
10:45 - 11:15 Group exercise introduction Slides
11:15 - 12:30 Begin group exercise Exercise, Optional datasets: Survey data, post-stratification data (Not open to public/No livestream)
12:30 - 1:30 Lunch
1:30 - 3:15 Continue group exercise (Not open to public/No livestream)
3:15 - 3:45 Discuss activity and open-source data Slides
3:45 - 4:00 Break
4:00 - 5:30 Guest speaker: Justin Grimmer
6:00 - 7:30 Dinner & Discussion (Not open to public/No livestream)
9:00 - 9:15 Logistics (Not open to public/No livestream)
9:15 - 9:45 Mass collaboration Slides
9:45 - 10:15 The Fragile Families Challenge Slides
10:15 - 10:30 Coffee break
10:30 - 11:30 Participating in the Fragile Families Challenge Activity Slides
11:30 - 12:30 A Brief Introduction to Machine Learning with Georgiy Bobashev, Center for Data Science at RTI Slides
12:30 - 1:30 Lunch
1:30 - 2:30 Drone Data Workshop
2:30 - 2:45 Break
2:45 - 3:45 Synthetic Populations Workshop Slides
3:45 - 4:30 Tour of RTI
4:30 - 5:30 Guest speaker: Annie Liang (Princeton livestream)
9:00 - 9:15 Logistics (Not open to public/No livestream)
9:15 - 9:30 What, why, and which experiments? Slides
9:30 - 9:45 Moving beyond simple experiments Slides
9:45 - 10:15 Four strategies for making experiments happen Slides
10:15 - 10:30 Coffee break
10:30 - 11:00 Zero variable cost data and musiclab Slides
11:00 - 11:15 Break
11:15 - 12:15 High-throughput behavioral science using virtual labs by guest speaker Abdullah Almaatouq (SICSS 2017)
12:15 - 12:30 Get lunch from cafeteria
12:30 - 1:30 Lunch and guest speaker: Eric Schwartz (Editorial Director, Columbia University Press). Why and How to Publish a Book with a University Press
1:30 - 2:30 Research Speed Dating (Not open to public/No livestream)
2:30 - 4:30 Groups start work
4:30 - 5:00 Wrap-up and Discussion
12:30 - 2:00 Lunch and Guest Speaker: Chris Wiggins. What should future statisticians CEOs, and senators know about the history and ethics of data? (Princeton livestream)
3:30 - 4:00 Group Check-in
10:00 - 10:30 Introduction to Git Github (Emily Hadley)
11:45 - 12:30 Voluntary Job Market Lunch Discussion
12:30 - 1:30 Multi-site panel discussion about navigating the job market featuring Chris Bail, Karen Davis, Ridhi Kashyap, and Matti Nelimarkka (Note this requires a new kind of livestream and it might not work right)
1:30 - 2:00 Flash talks from RTI Center For Data Science: Peter Baumgartner: Lessons for Applied Natural Language Processing, Emily Hadley: Machine Learning for Medical Auto-Coding, Jason Nance: Deep Learning ToolKit: Accessible deep learning experimentation
2:00 - 2:30 Group check-in
3:30 - 5:00 Small Group Virtual Reality Lab Tours
12:45 - 1:30 Flash Talks - Using R to Run, Collect, and Summarize Data from External Programs (Derek Ramirez), Epidemiology Meets Econometrics: Simulation Methods for Food Policy Impact Evaluation (Ben Allaire), Open Source Knowledge Enrichment (Felecia Vega)
1:30 - 2:00 Group Check-in
3:30 - 5:00 Small Group Virtual Reality Lab Tours
1:30-2:00 Modeling Student Preference in College Proximity to Home: A Synthetic Population Application (Tara Weatherholt, Derek Ramirez, Nestor Ramirez, Becca Merrill), 2:00-2:30 Estimating the Undocumented Immigrant Population and Examining News Discourse in North Carolina through Machine Learning (Felecia Vega, Chris Inkpen, Marwa Salem, Siri Warkentien), 2:30-3:00 Probing the Relationship of Twitter Disinformation and News Discourse (Elena Leonchuk, Zhifan Luo, Ioanna Pavlidou, Jonathan Schlosser), 3:00-3:30 Predicting Stars: A Text Analysis of Yelp Reviews (Claire Chipman Gilliland, Ria Kontou, Helen Liu, Chao Liu, Eugene Uwiragiye, Qinghua Yang, Ben Allaire, Lawrence Whitley), 3:30-4:00 Bioengineered Food Label Study (Sophie Kelmenson, Samantha Mosier), 4:00-4:30 Automated Evaluation of Party Manifestos (Michelle Corea, Molly Jacobs, Tim McDade, Mateo Villamizar Chaparro, Kyle Chan)
You can host a partner location of the Summer Institutes of Computational Social Science (SICSS) at your university, company, NGO, or government agency.