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Sid Jha and Matt Nicholson present at Northwestern Computational Research Day
Sid Jha will give a lightning talk “A Computational Platform to Evaluate the Ability to Perceive Social Connections” at the 2018 Computational Research Day on April 10, 2018. Moreover, Sid and Matt (both Undergraduate Research Assistants at SONIC) will present their posters then, respectively:
- Creating a Framework for Evaluating the Effectiveness of Various Search Strategies in the Small-World Phenomenon (by Matt)
- Network Acuity: Social Perceptions in a Small-World Experiment (by Sid)
Both abstracts and posters are available: http://computational-research-day.s3-website.us-east-2.amazonaws.com/posters/
Jeremy Foote presents at iConference 2018
Jeremy Foote attended iConference on March 27, 2018 in Sheffield, UK where he presented work on characterizing founders of online peer production communities, coauthored with Noshir Contractor.
Foote, J., Contractor, N. The Behavior and Network Position of Peer Production Founders.
Computational Social Science ≠ Computer Science + Social Data
Hanna Wallach published a thought piece of what computational social science is, especially from her computer science point of view. Given computational social science in mind, She made points of differences between computer science and social science in terms of goals, models, data, and challenges:
- Goals: Prediction vs. explanation — “[C]omputer scientists may be interested in finding the needle in the haystack—such as […] the right Web page to display from a search—but social scientists are more commonly interested in characterizing the haystack.”
- Models: “Models for prediction are often intended to replace human interpretation or reasoning, whereas models for explanation are intended to inform or guide human reasoning.”
- Data: “Computer scientists usually work with large-scale, digitized datasets, often collected and made available for no particular purpose other than “machine learning research.” In contrast, social scientists often use data collected or curated in order to answer specific questions.”
- Challenges: Datasets consisting of social phenomena raised ethical concerns regarding privacy, fairness, and accountability — “they may be new to most computer scientists, but they are not new to social scientists.”
She concludes her article saying that “we need to work with social scientists in order to understand the ethical implications and consequences of our modeling decisions.”
The article is available here.
Cooperation, clustering, and assortative mixing in dynamic networks
A recent study by David Melamed and his colleagues examined whether the emergent structures that promote cooperation are driven by reputation or can emerge purely via dynamics. To answer the research question, they recruited 1,979 Amazon Mechanical Turkers and asked them to play an iterated prisoner’s dilemma game. Further, these participants were randomly assigned one of 16 experimental conditions. Results of the experiments show that dynamic networks yield high rates of cooperation even without reputational knowledge. Additionally, the study found that the targeted choice condition in static networks yields cooperation rates as high as those in dynamic networks.
The original article is available here.
Jackie Ng is going to Harvard’s LISH in Fall 2018
SONIC lab member Jackie Ng has accepted a postdoctoral fellowship with the Laboratory for Innovation Science (LISH) at Harvard University starting in Fall 2018. Congratulations!
Jacqueline Ng and Diego Gómez-Zará presented at the ATLAS’s Teams Research Incubator Weekend
Jacqueline Ng, Ph.D. candidate, and Diego Gómez-Zará, Ph.D. student, presented their current research at the ATLAS’s Teams Research Incubator for doctoral students and junior faculty, in Evanston, IL
On March 17th, Jacqueline presented “Information sharing in online teams: How information processing interventions affect team discussions” in a session titled “Multilevel Perspectives on Teams.”
Then, on March 18th, Diego presented his work on team recommender systems: “Social Cognition and Team Assembly:
Competence, Warmth, or Embeddedness.” The session was titled “Perceptions & Teams.”
Students’ social interactions and daily routines to make predictions about freshman retention
Sudha Ram’s Smart Campus research tracks students’ social interactions and daily routines via their CatCard usage — and leverages that information to make predictions about freshman retention. The goal of Ram’s Smart Campus research is to help educational institutions repurpose the data already being captured from student ID cards to identify those most at risk for not returning after their first year of college. Ram found that social integration and routine were stronger predictors than end-of-term grades, which is one of the more traditionally used predictors of freshman retention in higher education.
Read the article here.
SONIC’s paper published in Communication Methods and Measures
A paper co-authored by SONIC’s Alina Lungeanu, Noshir Contractor, ATLAS’ Leslie DeChurch, and UGA’s Dorothy Carter was published in the journal Communication Methods and Measures.
Lungeanu, A., Carter, D. R., DeChurch, L. A., & Contractor, N. S. (2018). How Team Interlock Ecosystems Shape the Assembly of Scientific Teams: A Hypergraph Approach. Communication Methods and Measures, 1-25.
SONIC presents at the Organizational Science Winter Conference in Utah
SONIC members, Jacqueline Ng and Noshir Contractor, are coauthors along with Leslie DeChurch (ATLAS, Northwestern) and Paul Leonardi (UCSB) of “The Sociomateriality of Teamwork” presented at the Organizational Science Winter Conference on the theme “Technology and the Modern Organization” on March 2nd, 2018 in Park City, Utah.
SONIC hosts a Relational Event Modeling research incubator
SONIC hosted a Relational Event Modeling research incubator on Feb 23rd and Feb 24th where 10 researchers from the US Army Research Lab, Stanford, University of Georgia, Purdue and Northwestern discussed how recent advances in relational event modeling can be leveraged to address their research questions and how novel research questions can in turn prompt methodological advances in relational event modeling.