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.
@article{arxiv.2505.15563,
title = {Semantic-based Unsupervised Framing Analysis (SUFA): A Novel Approach for Computational Framing Analysis},
author = {Mohammad Ali and Naeemul Hassan},
journal= {arXiv preprint arXiv:2505.15563},
year = {2025}
}
Comments
Association for Education in Journalism and Mass Communication (AEJMC) Conference, August 07--10, 2023, Washington, DC, USA