Category: Discovery & Impact

Title: Network Analysis in Python

Date Published: February 8, 2019

Last week, the Massive Data Institute held its second two-day data workshop that focused on teaching students, faculty, and staff about how to conduct network analysis in Python. Led by Dr. Laila Wahedi, MDI Fellow, the workshops taught network construction, descriptive analysis, adding network variables to regression analyzes, and basic network visualization.

Laila Wahedi leading data workshop as participants seated listen.

The first workshop, held on Friday, January 25, focused on helping attendees identify relational data to use in network analysis. Participants learned to construct networks from their data, and also learned methods to best describe their networks and gain valuable tools to help further their research goals. The second workshop, held Friday, February 15, was dedicated to make inferences from collected network data. The workshop helped attendees understand network questions and how they relate to social science or public policy questions in which students may be interested. Dr. Wahedi showed participants how to construct hypotheses and then test them by comparing expected trends in network structure to the structure of appropriate random networks. Access these two data workshops here.