Semantic-based Unsupervised Framing Analysis (SUFA): A Novel Approach for Computational Framing Analysis
arXiv:2505.15563
Abstract
This research presents a novel approach to computational framing analysis, called Semantic Relations-based Unsupervised Framing Analysis (SUFA). SUFA leverages semantic relations and dependency parsing algorithms to identify and assess entity-centric emphasis frames in news media reports. This innovative method is derived from two studies -- qualitative and computational -- using a dataset related to gun violence, demonstrating its potential for analyzing entity-centric emphasis frames. This article discusses SUFA's strengths, limitations, and application procedures. Overall, the SUFA approach offers a significant methodological advancement in computational framing analysis, with its broad applicability across both the social sciences and computational domains.
Association for Education in Journalism and Mass Communication (AEJMC) Conference, August 07--10, 2023, Washington, DC, USA