What can tripartite semantic network analysis do for media framing research?
Issue Date: 
2020
Publisher: 
Servicio de Publicaciones de la Universidad de Navarra
ISSN: 
2386-7876
Citation: 
Shin, Y. (Yongjun). "What can tripartite semantic network analysis do for media framing research?". Communication & Society. 33 (1), 2020, 121 - 137
Abstract
This study primarily aims to demonstrate how tripartite semantic network analysis can help us with media framing analysis. Predominant quantitative framing research has tended to focus on identifying salient frames and/or assessing their influences on public opinions. Also, semantic network analysis has been used to display relationships among frames, which complements conventional quantitative frame analysis for frequency and salience of frames. However, it needs to be advanced in the way that it can assess the dynamical relationships among actors, frames, and the actors’ stances on an issue. In this vein, it is encouraging to find that Robert Entman has demonstrated the dynamics in framing and the complicated relationships between frames and actors in different social realms through his cascading activation model. Tripartite semantic network analysis is expected to contribute to systematically depicting the complicated framing relationships in the form of network. This research attempts to showcase how tripartite semantic analysis can complement framing analysis through a case study on a controversial local housing policy in Madison, Wisconsin, USA. While the descriptive statistical analyses show the overall differences in framing across the newspapers and the changes in framings over time, the tripartite semantic network analyses display delicate and significant differences and changes in framing, which is hard to be captured in quantitative framing analysis. It might also be valuable for not only research but also more effective engagement in public discourses.

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