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The work introduces a new corpus for Slavic languages, covering Bulgarian, Polish, and Russian documents from parliamentary debates and social media. Texts are annotated at both the coarse-grained text-span level and the fine-grained sentence level, using 25 fine-grained persuasion techniques organized into six broad strategy categories. The paper details corpus creation, provides statistics and topic–technique correlations, and establishes ML and generative-AI baselines for detection and classification.","arXiv :2607 . 107 15v 1 [ cs .CL] 12 Jul 2026  \nA Corpus of Persuasion Techniques in Slavic Languages  \nJakub Piskorski⋆ , Dimitar Iliyanov Dimitrov†, Marina Ernst‡, Jacek Haneczok♢ , Michał Marci czuk♠ , Arkadiusz Modzelewski§ ,  \nRoman Yangarber♡  \n⋆ Institute of Computer Science, Polish Academy of Science, Poland,†Sofia University \"St. Kliment Ohridski\", Bulgaria, ‡ University of Koblenz, Germany,♢ Visa Technology Europe, ♠ CodeNLP,  \n§ University of Padua, Italy, ♡ University of Helsinki, Finland  \njpiskorski@gmail.com, ilijanovd@fmi.uni-sofia.bg, marinaernst@uni-koblenz.de, [jacek.haneczok@gmail.com](jacek.haneczok@gmail.com), [marcinczuk@gmail.com](marcinczuk@gmail.com), [contact@amodzelewski.com](contact@amodzelewski.com),  \n[roman.yangarber@helsinki.fi](roman.yangarber@helsinki.fi)  \nAbstract  \nPersuasion techniques are powerful rhetorical devices used to sway public opinion in a wide range of media. We present a new corpus of persuasion techniques, focusing on Slavic languages. The corpus contains documents in Bulgarian, Polish, and Russian, annotated with persuasion techniques at the coarse-grained text-span level and fine-grained sentence level. The techniques are drawn from a taxonomy of 25 fine-grained persuasion techniques, grouped under six broad categories of rhetorical persuasion strategies. The corpus contains approximately 7500 text spans from 222 documents that cover topics hotly debated at the national and international levels. We describe the corpus creation process, provide detailed statistics, and examine correlations between topics and persuasion techniques. We use classic ML-based and generative AI-based models to provide baselines and benchmark results for the detection and classification of persuasion techniques at the text-span level and sentence level.  \nKeywords: persuasion techniques, text classification, linguistic resources, Slavic languages, machine learning  \n1. Introduction  \nPersuasion is central to political debates, affecting policy outcomes, and is heavily used in a wide range of contexts, including by social media influencers, to sway public opinion. Persuasion techniques function as psychological mechanisms designed to steer the reader’s beliefs and actions, such as voting. Many are based on flawed or unsound reasoning in constructing arguments, while others deliberately trigger emotional responses—such as appeal to patriotism—to secure agreement when factual support is missing or weak.  \nIn this paper, we present a new corpus of texts annotated with persuasion techniques in Slavic languages. It contains documents from parliamentary debates in Bulgarian and Polish, and social media in Russian, annotated with persuasion techniques, using a taxonomy of 25 fine-grained persuasion techniques. The corpus consists of approximately 7,500 text fragments annotated with persuasion techniques, in 222 documents. The corpus covers highly debated topics at the international—e.g. , the Ukraine-Russia war—and national level—e.g. , abortion legislation.  \nThe main impetus behind the creation of the presented corpus is to foster and stimulate research on the detection of persuasion techniques and the classification of texts in Slavic languages. We aim to cover the domains of parliamentary debates  \nand social media, for which there are few or no resources on persuasion techniques in Slavic languages. Our contributions can be summarized as follows:  \n• we release a new corpus of persuasion techniques, annotated at the text-span and sentence level in three Slavic languages—Bulgarian, Polish, and Russian—for two text genres: parliamentary debates and social media posts,  \n• we provide the characteristics of this corpus, including statistics, topics, and correlations among the labels,  \n• we release and evaluate classical ML- and generative-AI-based baseline models for detection and classification of persuasion techniques at the text-span and sentence levels.  \nIt is important to emphasize that text-span a","cbCaiooRGcatlacc","https://ap.wps.com/l/cbCaiooRGcatlacc","pdf",821414,3,1,18,"English","en",105,"# Introduction\n# Related Work\n# Corpus Creation\n# Correlations Between Topics and Techniques\n# Baseline Models and Experiments\n# Conclusion and Future Work","[{\"question\":\"What languages and data sources does the corpus cover?\",\"answer\":\"The corpus includes documents in Bulgarian, Polish, and Russian, drawn from parliamentary debates and social media posts.\"},{\"question\":\"How are persuasion techniques annotated in the corpus?\",\"answer\":\"Annotations are provided at two granularities: text-span level and sentence level, where sentence labels are obtained by mapping text spans to sentences.\"},{\"question\":\"What is the persuasion technique taxonomy used in this corpus?\",\"answer\":\"The taxonomy contains 25 fine-grained persuasion techniques grouped into six broad categories of rhetorical persuasion strategies.\"}]",1784212294,45,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-corpus-of-persuasion-techniques-in-slavic-languages","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,50],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":20},"https://docshare.wps.com/document/research-report/",{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/a-corpus-of-persuasion-techniques-in-slavic-languages/86511/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-28","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What languages and data sources does the corpus cover?","Question",{"text":75,"@type":76},"The corpus includes documents in Bulgarian, Polish, and Russian, drawn from parliamentary debates and social media posts.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How are persuasion techniques annotated in the corpus?",{"text":80,"@type":76},"Annotations are provided at two granularities: text-span level and sentence level, where sentence labels are obtained by mapping text spans to sentences.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the persuasion technique taxonomy used in this corpus?",{"text":84,"@type":76},"The taxonomy contains 25 fine-grained persuasion techniques grouped into six broad categories of rhetorical persuasion 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