Semantic-based Unsupervised Framing Analysis (SUFA): A Novel Approach for Computational Framing Analysis
Year: 2025
Type: preprint
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.
Source: arXiv (Cornell University)
Authors: Ali, Mohammad, Hassan, Naeemul
Institution: University of Maryland, College Park
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4415329115