August 13, 2018 - August 17, 2018
8:00 - 9:00: Breakfast
9:00 - 10:00: Logistics, administrivia, introductions [Slides]
10:00 - 11:00: Round robin of participant’s research and how it relates to the topic of the day [Activity]
11:00 - 12:00: Lecture 1 - Principles of ethics, four areas of difficulty (consent, risk, privacy, uncertainty) [Slides]
12:00 - 1:00: Lunch
1:00 - 2:00: Lecture 2 - Contextual integrity, value-sensitive design, regulatory models, de-anonymization, social engineering, incentives [Slides]
2:00 - 3:00: Case Study 1 - Users behaving badly [Activity]
3:00 - 3:30: Coffee break
3:30 - 4:30: Case Study 2 - Researchers behaving badly [Activity]
4:30 - 5:30: Research Talk - Casey Fiesler [Slides]
8:00 - 9:00: Breakfast
9:00 - 10:00: Round robin of participant’s research and how it relates to the topic of the day [Activity]
10:00 - 11:00: Lecture 1 - Introduction to digital trace data & web scraping [Slides]
11:00 - 12:00: Case Study 1 - Scraping web sites (rate limits, messy data, TOS) [Activity]
12:00 - 1:00: Lunch
1:00 - 2:00: Lecture 2 - Application programming interfaces (JSON, keys, rate limits) [Slides]
2:00 - 3:00: Case Study 2 - Application of API scraping [Materials]
3:00 - 3:30: Coffee break
3:30 - 4:30: Research Talk - Yotam Shmargad [Slides]
4:30 - 5:30: Research Talk - Brian Keegan [Materials]
8:00 - 9:00: Breakfast
9:00 - 10:00: Round robin of participant’s research and how it relates to the topic of the day [Activity]
10:00 - 11:00: Case Study 1 - Networkx and using ICON (https://icon.colorado.edu/) [Activity]
11:00 - 12:00: Lecture 1 - Introduction to networks [Slides]
12:00 - 1:00: Lunch
1:00 - 2:00: Lecture 2 - Community detection and hierarchies [Slides]
2:00 - 3:00: Case Study 2 - Generating rankings using pairwise comparisons [Materials]
3:00 - 3:30: Coffee break
3:30 - 4:30: Research Talk - Aaron Clauset [Slides]
4:30 - 5:30: Research Talk - Dan Larremore [Slides]
8:00 - 9:00: Breakfast
9:00 - 10:00: Round robin of participant’s research and how it relates to the topic of the day [Activity]
10:00 - 11:00: Lecture 1 - Text processing (casing, tokenizing, n-grams, stemming, regex, TF-IDF) [Materials]
11:00 - 12:00: Lecture 2 - Sentiment analysis [Materials]
12:00 - 1:00: Lunch
1:00 - 2:00: Lecture 3 - Text networks and word embeddings [Materials]
2:00 - 3:00: Case Study 2 - Cleaning and analysis of presidental text [Materials]
3:00 - 3:30: Coffee break
3:30 - 4:30: Research Talk - Chenhao Tan [Slides]
8:00 - 9:00: Breakfast
9:00 - 10:00: Round robin of participant’s research and how it relates to the topic of the day [Activity]
10:00 - 11:00: Lecture 1 - Experimental design (RCTs, factorial design, validity etc.), A-B tests [Slides]
11:00 - 12:00: Lecture 2 - Causal inference from observational data (discontinuity, instrumental variable, matching, differencing) [Slides]
12:00 - 1:00: Lunch
1:00 - 2:00: Case Study 2 - Examine natural experiments in time series data [Activity]
2:00 - 3:00: Research Talk 1 - Jake Hofman [Slides]
3:00 - 3:30: Coffee break
3:30 - 4:30: Research Talk 2 - Amanda Stevenson
4:30 - 5:30: Short research talks by participants, wrapping things up
You can host a partner location of the Summer Institutes of Computational Social Science (SICSS) at your university, company, NGO, or government agency.