- “#FailedRevolutions: Using Twitter to Study the Antecedents of ISIS Support,” Walid Magdy, Qatar Computing Research Institute; Kareem Darwish; Ingmar Weber, Qatar Computing Research Institute
- “Actually, It’s About Ethics in Computational Social Science: A Multi-party Risk-Benefit Framework for Online Community Research,” Brian Keegan, Harvard Business School; J. Nathan Matias, MIT Media Lab
- “Characterizing the Demographics Behind the #BlackLivesMatter Movement,” Alexandra Olteanu, EPFL; Ingmar Weber, QCRI; Daniel Gatica-Perez, IDIAP
- “Computational Causal Inference in Populations of Quasi-Experiments,” Aaron Shaw, Northwestern University; Benjamin Mako Hill, University of Washington
- “Cultural Influences on the Measurment of Personal Values through Words,” Rada Mihalcea, University of Michigan
- “Does Copyright Affect Reuse? Evidence from the Google Books Digitization Project,” Abhishek Nagaraj, MIT
- “Emoticons vs. Emojis on Twitter: A Causal Inference Approach,” Umashanthi Pavalanathan, Georgia Institute of Technology; Jacob Eisenstein, Georgia Institute of Technology
- “Enhancing Validity in Observational Settings When Replication Is Not Possible,” Christopher Fariss, Penn State University; Zachary Jones, Penn State University
- “Estimating the causal impact of recommendation systems from observational data,” Amit Sharma, Microsoft Research; Jake Hofman, Microsoft Research; Duncan Watts, Microsoft Research
- “Geolocated Twitter Panels to Study the Impact of Events,” Han Zhang, Princeton University; David Rothschild, Microsoft Research; Shawndra Hill, Microsoft Research
- “Identifying social influence in online activity feeds: Preference-based Matched Estimation,” Amit Sharma, Microsoft Research; Dan Cosley, Cornell University
- “Left-handed or Right-handed? A Data-driven Approach to Analysing Characteristics of Handedness based on Language Use,” Ho-gene Choe, University of Michigan; Rada Mihalcea, University of Michigan
- “Predicting Student Engagement Through Trace Data,” Jeffrey Rokkum, Iowa State University; Reynol Junco, Iowa State University
- “Reducing confounding bias in observational studies that use text classification,” Virgile Landeiro, Illinois Institute of Technology; Aron Culotta, Illinois Institute of Technology
- “Risk Sharing and Mobile Phones: Evidence in the Aftermath of Natural Disasters,” Joshua Blumenstock, University of Washington; Marcel Fafchamps, Stanford University; Nathan Eagle, Santa Fe Institute
- “Structural Causes of Bias in Crowd-derived Geographic Information: Towards a Holistic Understanding,” Isaac Johnson, University of Minnesota; Brent Hecht, University of Minnesota
- “The Monetization of Information Broadcasts: A Natural Experiment on an Online Social Network,” Yotam Shmargad, University of Arizona
- “The Spread of Cooperation: Peer Effects in Gift Giving,” Rene Kizilcec, Stanford University; Eytan Bakshy, Facebook; Dean Eckles, MIT; Moira Burke, Facebook
- “Towards Real-Time Measurement of Public Epidemic Awareness: Monitoring Influenza Awareness through Twitter,” Michael Smith, George Washington University; David Broniatowski, George Washington University; Michael Paul, University of Colorado Boulder; Mark Dredze, Johns Hopkins University
- “Using Propensity Score Matching to Understand the Relationship Between Online Health Information Sources and Vaccination Sentiment,” Nabeel Rehman, New York University; Jason Liu, New York University; Rumi Chunara, New York University