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ACL 2026longmain

DiNO: Disinformation Narrative Observer

Witold Sosnowski, Arkadiusz Modzelewski, Kinga Skorupska, Adam Wierzbicki

Polish-Japanese Institute of Information Technology in Warsaw

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2026.acl-long.2160 ↗

摘要

Disinformation is an escalating global threat, making it essential to understand its content, dissemination, and evolution. To confront this challenge, researchers have begun grouping related false claims into broader disinformation narratives, which can be tracked across cultures, time periods, and media sources. Analyzing these narratives provides critical insights for developing more effective countermeasures. To this end, we introduce DiNO: Disinformation Narrative Observer, a novel method designed to extract disinformation narratives from news articles. We applied DiNO to news articles on the Ukraine War, COVID-19 and Migration, sourced from disinformation-prone outlets as well as a reputable source. We evaluated the narratives extracted by DiNO by measuring how well their topics and stances aligned with a recognized disinformation narratives dataset. DiNO outperforms competitive narrative mining approaches, including Relatio and CaNarEx, achieving a 41%–44% improvement in topical alignment and a 30%–41% improvment in stance alignment.