@inproceedings{fiumano-etal-2026-victim,
title = "Victim or Assailant? Exploring Narratives through Knowledge Graph Queries",
author = "Fiuman{\`o}, Beatrice and
Lazzari, Nicolas and
Ponzetto, Simone Paolo and
Presutti, Valentina",
editor = "McCrae, John P. and
Gkirtzou, Katerina and
Khan, Fahad and
Martin Chozas, Patricia and
Carvalho, Sara and
Canning, Erin",
booktitle = "Proceedings of 10th Workshop on Linked Data in Linguistics ({LDL}-2026)",
month = may,
year = "2026",
address = "Palma, Mallorca (Spain)",
publisher = "ELRA Language Resources Association (ELRA)",
url = "https://aclanthology.org/2026.ldl-1.5/",
doi = "10.63317/22ezaux6id7v",
pages = "40--49",
abstract = "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 \url{https://github.com/beatrice-f/DORIS/}."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="fiumano-etal-2026-victim">
<titleInfo>
<title>Victim or Assailant? Exploring Narratives through Knowledge Graph Queries</title>
</titleInfo>
<name type="personal">
<namePart type="given">Beatrice</namePart>
<namePart type="family">Fiumanò</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nicolas</namePart>
<namePart type="family">Lazzari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Simone</namePart>
<namePart type="given">Paolo</namePart>
<namePart type="family">Ponzetto</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Valentina</namePart>
<namePart type="family">Presutti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-05</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of 10th Workshop on Linked Data in Linguistics (LDL-2026)</title>
</titleInfo>
<name type="personal">
<namePart type="given">John</namePart>
<namePart type="given">P</namePart>
<namePart type="family">McCrae</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Katerina</namePart>
<namePart type="family">Gkirtzou</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Fahad</namePart>
<namePart type="family">Khan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Patricia</namePart>
<namePart type="family">Martin Chozas</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sara</namePart>
<namePart type="family">Carvalho</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Erin</namePart>
<namePart type="family">Canning</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>ELRA Language Resources Association (ELRA)</publisher>
<place>
<placeTerm type="text">Palma, Mallorca (Spain)</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>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/.</abstract>
<identifier type="citekey">fiumano-etal-2026-victim</identifier>
<identifier type="doi">10.63317/22ezaux6id7v</identifier>
<location>
<url>https://aclanthology.org/2026.ldl-1.5/</url>
</location>
<part>
<date>2026-05</date>
<extent unit="page">
<start>40</start>
<end>49</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Victim or Assailant? Exploring Narratives through Knowledge Graph Queries
%A Fiumanò, Beatrice
%A Lazzari, Nicolas
%A Ponzetto, Simone Paolo
%A Presutti, Valentina
%Y McCrae, John P.
%Y Gkirtzou, Katerina
%Y Khan, Fahad
%Y Martin Chozas, Patricia
%Y Carvalho, Sara
%Y Canning, Erin
%S Proceedings of 10th Workshop on Linked Data in Linguistics (LDL-2026)
%D 2026
%8 May
%I ELRA Language Resources Association (ELRA)
%C Palma, Mallorca (Spain)
%F fiumano-etal-2026-victim
%X 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/.
%R 10.63317/22ezaux6id7v
%U https://aclanthology.org/2026.ldl-1.5/
%U https://doi.org/10.63317/22ezaux6id7v
%P 40-49
Markdown (Informal)
[Victim or Assailant? Exploring Narratives through Knowledge Graph Queries](https://aclanthology.org/2026.ldl-1.5/) (Fiumanò et al., LDL 2026)
ACL