2.019 - PDC11: Network Analysis of Qualitative Data (NAQD): Toward Multimodal Narratives to Democratize Evidence

Session Type: Professional Development Course

Abstract

Network analysis is an increasingly important analytic approach utilized to find structure in relationships that, due to their complexity and/or dimensionality, are hidden at first glance. The goal of this course is to teach participants how to harness the mathematical power of network analysis in order to find structure in written content. This analytic method (Network Analysis of Qualitative Data ---NAQD) blends quantitative, mathematical, and qualitative principles to analyze text data, which is an approach yet to be broadly implemented in education research.

The course relies on both lecture and hands-on exercises. All data and software are freely available, which liberates participants from the need to spend hundreds or thousands of dollars to conduct analyses. Throughout the course, the analysis and interpretation of data will be prioritized. Once participants have mastered the network concepts covered ---including measures of centrality and network visualization-- the course will move toward the application of these principles and techniques to highlight the most important actors, codes, and words in a dataset.

This course is appropriate for graduate students, early career scholars, and advanced researchers. The course will be based on the use of R, but requires no previous familiarity with the software. A quick R tutorial will be provided along with all the code and data required to replicate the exercises. Participants are required to bring their computers and must be able to install software. Assignments entail replicating and interpreting the in-class analyses with an emphasis on the relevance of discovered network structures.

Sub Unit

• Professional Development and Training Committee

Director

• Manuel S. Gonzalez Canche, University of Pennsylvania