An Introduction to Social Network Analysis

Social Network Analysis (SNA) is a powerful and generalizable method that allows insight into the complicated patterns found within social connection data. This session will introduce SNA for a beginner audience; including how to structure data before building a network, calculating and interpreting basic network statistics, and commonly used tools and technologies. A number of applied examples from across industry and academia, including a personal project focused on LGBTQ+ health, will demonstrate the versatility of SNA. An accompanying demo that walks through creating, visualizing, and analyzing social networks in Python will be briefly discussed and shared during the meetup.

Kelsey Campbell is a data scientist and founder of Gayta Science, a site devoted to highlighting the LGBTQ+ experience using data science and analytics. With a growing team of volunteer analysts, designers, researchers, and developers, Gayta Science is devoted to investigating a variety of LGBTQ+ issues using data-driven techniques and open-source technology. Kelsey has professional experience utilizing data in custom software solutions and public health research. They hold a M.S. in Analytics from the Institute for Advanced Analytics at NC State University and a B.S. in Economics from Purdue University.