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LITUND: Lithuanian Unreliable News Detection Corpus
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Abstract: This paper introduces LITUND, a dedicated corpus of unreliable news texts in the Lithuanian language, developed to support linguistic and interdisciplinary research on disinformation. Today unreliable information tools and corpora are mostly available for high-resource languages and Lithuanian remains underrepresented in this area. The LITUND corpus was compiled using texts sourced from Lithuanian media outlets that were identified as misleading by professional fact-checkers. The compilation process involved a manual search for disinformation across multiple platforms and search engines, as well as critical decisions regarding source selection, categorization, and verification. This paper is dedicated to outlining the methodology behind corpus construction, discussing the encountered challenges and reflecting on the implications for future research. LITUND is intended to serve as an open resource for studying the linguistic features of unreliable content and to support the development of NLP tools, media literacy efforts, and cross-disciplinary analyses of disinformation in low-resource language settings.
Keywords: unreliable news, disinformation, unreliable information, cross-disciplinary analyses, LITUND corpus, Lithuanian media.
Title: LITUND: Lithuanian Unreliable News Detection Corpus
Description:
Abstract: This paper introduces LITUND, a dedicated corpus of unreliable news texts in the Lithuanian language, developed to support linguistic and interdisciplinary research on disinformation.
Today unreliable information tools and corpora are mostly available for high-resource languages and Lithuanian remains underrepresented in this area.
The LITUND corpus was compiled using texts sourced from Lithuanian media outlets that were identified as misleading by professional fact-checkers.
The compilation process involved a manual search for disinformation across multiple platforms and search engines, as well as critical decisions regarding source selection, categorization, and verification.
This paper is dedicated to outlining the methodology behind corpus construction, discussing the encountered challenges and reflecting on the implications for future research.
LITUND is intended to serve as an open resource for studying the linguistic features of unreliable content and to support the development of NLP tools, media literacy efforts, and cross-disciplinary analyses of disinformation in low-resource language settings.
Keywords: unreliable news, disinformation, unreliable information, cross-disciplinary analyses, LITUND corpus, Lithuanian media.
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