SONIC Lab presented the results of My Dream Team case study at CITEP, Argentina.

On April 9th, Professor Noshir Contractor and his Ph.D. student Diego Gómez-Zará presented the results of the team assembly case study conducted at the Center for Technological and Pedagogical Innovation (CITEP – Centro de Innovación en Tecnología y Pedagogía). The talk was given at the University of Buenos Aires in Buenos Aires, Argentina. Noshir and Diego presented how the participants of this academic program searched and invited others to assemble teams. The main results explain the relevant features for creating effective teams and demonstrate how My Dream Team –a web-based teaming search platform– facilitate the formation of teams in educational contexts.

 

 

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Diego Gómez-Zará presents at INGroup 2018

Diego Gómez-Zará is going to attend the 13th Annual INGRoup Conference on July 18-22, in Washington, DC. He will present one of the My Dream Team project’s publications called “Social Cognition and Team Assembly: Competence, Warmth, or Embeddedness,” co-authored with Jacqueline Ng, Marlon Twyman, Silvia Andreoli, Leslie DeChurch, and Noshir Contractor.

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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/

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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.

 

 

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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.

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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.

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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.
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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.

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