Victim or Assailant? Exploring Narratives through Knowledge Graph Queries

Our understanding of social reality is shaped by the specific ways in which that reality is framed by different sources. Analyzing framing means examining how these sources are able to convey particular worldviews by foregrounding or downplaying certain aspects of experience. Current computational approaches address this task by automatically identifying communicative patterns (e.g., topic selection or rhetorical strategies) that characterize individual artifacts. However, they often remain document-bound, overlooking the comparative dimension that enables the uncovering of convergent or conflicting narratives about the same actor, event, or issue. In this paper, we propose DORIS, an ontology that supports both document-level and cross-document framing analysis using SPARQL queries on automatically constructed Knowledge Graphs. We validate the proposed approach through a case study of historical news articles, exploring multiple framings of a real-world event using Fillmore’s Frame Semantics and the FrameNet resource. Code and data are available on GitHub at https://github.com/beatrice-f/DORIS/.