Mixed Methods for Understanding Visual Frames in Social Movements by Laura W. Dozal

Bio: Laura W. Dozal is a third year PhD student at the UArizona iSchool. Her recent work has focused on analyzing and visualizing network clusters to understand social behavior. Her methods include deep learning for Natural Language Processing applications of online crime and disinformation and quantitative network analysis to identify community spaces.

Abstract: The interdisciplinary approach to understanding visual frames of social movement images through computational methods has the potential to communicate information on the actions, messages, and causes surrounding a movement by understanding how images are circulated throughout online networks. In this literature review, visual methods and computational analysis are explored to facilitate identification of frames that provide meaning for a user. Frame analysis and Gillian Rose’s Four Sites of a Critical Visual Methodology is reviewed and applied as a framework to analyze visual interpretation applications. The qualitative methods reviewed cover components of content analysis and technology in social movements. The quantitative methods reviewed consist of social network analysis applications of Exponential Random Graph Models (ERGM) and notions of position using block model analysis, as well as visual sentiment analysis using methods of neural networks in machine learning. Looking at visual frames through the lens of social movements opens space to review various types of applications for understanding how a visual can create meaning through perspective.


2 p.m. to 3 p.m. Feb. 18, 2022