Using Social Network Analysis to Model Online Interactions

Wednesday, March 28 | 2:30PM–3:15PM ET | Room 552
Session Type: Breakout Session
Delivery Format: Interactive Presentation
Social network analysis (SNA) refers to the methods applied to mapping and measuring connections and flows between network nodes (Hanneman 2017). We developed a self-service application that employs SNA approach to graphically analyze student online interactions with nodes representing individual students and links corresponding to direct interactions between students. In this session, we will demonstrate how to use the application to generate network diagrams with student online discussion data, and to identify "influential" students, subset groups, and peripheral nodes within a network. In the end, we will share an example of how faculty can leverage the results to inform discussion activities and evaluate the efficacy of discussion facilitation strategies.

Outcomes: Articulate the basic concept of Social Network Analysis (SNA) * Effectively use the application that we developed to graphically analyze discussion interaction data and interpret the diagrams/results * Apply the SNA results to enhance student interactions and learning communities


  • Jing Qi

    Learning Analytic and LMS Specialist, Dartmouth College
  • Brian Reid

    Associate Director of Geisel IT, Dartmouth College