Social Networks and Health 2024
Stream Links:
Day 1: https://www.youtube.com/watch?v=-pWgxNUQ1sA
Day 2: https://www.youtube.com/watch?v=TBqpWS6sJUE
Day 3: https://www.youtube.com/watch?v=dqr68F8QlD0
Day 4: https://www.youtube.com/watch?v=W73SUnDKKss
Lecturers and RAs:
James Moody, Director of Duke Network Analysis Center and Professor of Sociology, Duke University
Tom Wolff, Department of Sociology, Duke University
Madelynn Wellons, Department of Sociology, Duke University
Gabriel Varela, Department of Sociology, Duke University
Dana Pasquale, Department of Population Health Sciences, Duke University
Craig Rawlings, Department of Sociology, Duke University
Ashton Verdery, Department of Sociology and Criminology, Penn State
Tom Valente, Department of Preventive Medicine, University of Southern California
Scott Duxbury, Department of Sociology, University of North Carolina at Chapel Hill
Brea Perry, Department of Sociology, Indiana University
David Schaefer, Department of Sociology, University of California at Irvine
Michelle Anne Birkett, Department of Medical Social Sciences, Northwestern University
Lane Zook, Department of Sociology, University of South Carolina
Day 1:
Introduction; Background, Network Data 1 (James Moody, Duke University)
R-Lab: Data Entry & Organization Management (Liann Tucker, Duke University)
Network Metrics (centrality, cohesion) (James Moody, Duke University)
Ethics Discussion (Dana Pasquale, Duke University)
IDEANet Demo (Tom Wolff, Duke University)
Metrics Lab (Madelynn Wellons, Duke University)
Respondent Driven Sampling (RDS) Methods (Ashton Verdery, Penn State)
Data Collection (jimi adams, USC)
Day 2:
Ego Network Models (Brea Perry, Indiana University- Bloomington)
Ego Network Lab (Gabe Varela, Duke University)
Network Canvas (Michelle Birkett, Northwestern University)
New Directions in NSHAP (Ben Cornwell, Cornell University)
Community & Role Detection (James Moody, Duke University)
Community & Role Lab (Jon Morgan, Duke University)
Kinship Networks (Ashton Verdery, Penn State)
Day 3:
Regression with networks & missing data (James Moody, Duke University)
Peer Influence Models (Craig Rawlings, Duke University)
Introduction to statistical models for networks (James Moody, Duke University)
Network Interventions (Tom Valente)
Temporal Exponential Random Graph Models (TERGMs) Lecture and Lab (Scott Duxbury, UNC Chapel Hill)
Network Visualization (James Moody, Duke University)
Visualization Lab (Gabe Varela, Duke University)
Day 4:
SIENA Models (David Schaefer, UC Irvine)
SIENA Lab (David Schaefer, UC Irvine)
Simulation Models and ending Q+A (James Moody, Duke University)
