@inproceedings{scalvini-mashaghi-2025-semantic,
title = "Semantic Topology: a New Perspective for Communication Style Characterization",
author = "Scalvini, Barbara and
Mashaghi, Alireza",
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-acl.479/",
doi = "10.18653/v1/2025.findings-acl.479",
pages = "9223--9233",
ISBN = "979-8-89176-256-5",
abstract = "We introduce semantic topology, a novel framework for discourse analysis that leverages Circuit Topology to quantify the semantic arrangement of sentences in a text. By mapping recurring themes as series, parallel, or cross relationships, we identify statistical differences in communication patterns in long-form true and fake news. Our analysis of large-scale news datasets reveals that true news are more likely to exhibit more complex topological structures, with greater thematic interleaving and long-range coherence, whereas fake news favor simpler, more linear narratives. These findings suggest that topological features capture stylistic distinctions beyond traditional linguistic cues, offering new insights for discourse modeling."
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%0 Conference Proceedings
%T Semantic Topology: a New Perspective for Communication Style Characterization
%A Scalvini, Barbara
%A Mashaghi, Alireza
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Findings of the Association for Computational Linguistics: ACL 2025
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-256-5
%F scalvini-mashaghi-2025-semantic
%X We introduce semantic topology, a novel framework for discourse analysis that leverages Circuit Topology to quantify the semantic arrangement of sentences in a text. By mapping recurring themes as series, parallel, or cross relationships, we identify statistical differences in communication patterns in long-form true and fake news. Our analysis of large-scale news datasets reveals that true news are more likely to exhibit more complex topological structures, with greater thematic interleaving and long-range coherence, whereas fake news favor simpler, more linear narratives. These findings suggest that topological features capture stylistic distinctions beyond traditional linguistic cues, offering new insights for discourse modeling.
%R 10.18653/v1/2025.findings-acl.479
%U https://aclanthology.org/2025.findings-acl.479/
%U https://doi.org/10.18653/v1/2025.findings-acl.479
%P 9223-9233
Markdown (Informal)
[Semantic Topology: a New Perspective for Communication Style Characterization](https://aclanthology.org/2025.findings-acl.479/) (Scalvini & Mashaghi, Findings 2025)
ACL