Social Networks

BEBR’s Social Networks Program
Offers Personal And Professional Network Analysis And Visualization, As Well As Recommendations For Network Interventions.

Collaborations
- Center for the Humanities and the Public Sphere
- CTSI
- UF-FAMU-USC CaRE² Health Equity Center Program
- Biodiversity Institute
- University of Kentucky Center for Clinical and Translational Science
- University of Miami Clinical and Translational Science Institute
- Florida State University College of Medicine
Team
- Christopher McCarty
- Raffaele Vacca
- Mark Girson
- Ruijie Mao
- Till Krenz
- Tom Smith
- Jared Adams
Reports and Studies

As part of a research Project at the Center for the Humanities and the Public Sphere, data on the research interests, collaboration and topics of classes taught by

Using network science to identify and bridge scientific communities at a research university
Members of the Network Science Program at BEBR gave a presentation at the Translational Science 2018 conference on their data analysis and intervention strategies. The program aims to expand

The aim of this paper is to contribute to the understanding of the structural evolution of scientific collaboration networks. A large body of literature has focused on the

One truth new researchers quickly discover is that data collection is costly. In the social sciences, researchers expend copious amounts of time and grant money observing people, interviewing

A social network analysis of scientific collaborations at the University of Florida
Social Network Analysis (SNA) is a methodology and a theoretical perspective that studies patterns of relations among actors. When applied to the network of scientific collaborations at a

Designing a network intervention on the UF scientific network
Social Network Analysis is not just about describing and explaining networks, it is also about using networks for specific interventions with specific goals. Network interventions have traditionally been

Collaboration metrics from the UF network data, and their evolution
We used publicly available data on UF publications and grants to extract networks of collaborations among UF researchers in 2008-2012. This allowed us to define network metrics on