Combating Economic Disinformation with AI: Insights from the EkonInfoChecker Project
Vesna Buterin,
Dragan Čišić and
Ivan Gržeta ()
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Vesna Buterin: Faculty of Economics and Business, University of Rijeka, 51000 Rijeka, Croatia
Dragan Čišić: Faculty of Economics and Business, University of Rijeka, 51000 Rijeka, Croatia
Ivan Gržeta: Faculty of Economics and Business, University of Rijeka, 51000 Rijeka, Croatia
FinTech, 2025, vol. 4, issue 4, 1-17
Abstract:
Economic disinformation causes significant harm, resulting in substantial losses for the global economy. Each year, it is estimated that around USD 78 billion is lost due to the spread of false or misleading information, with a major share stemming from stock market fluctuations and misguided decisions. In Croatia, the rapid spread of economic misinformation further threatens decision-making and institutional credibility. The EkonInfoChecker project was established to address this issue by combining human fact-checking with AI-based detection. This paper presents the project’s AI component, which adapts English-language datasets (FakeNews Corpus 1.0 and WELFake) into Croatian, yielding over 170,000 articles in economics, finance, and business. We trained and evaluated six models—FastText, NBSVM, BiGRU, BERT, DistilBERT, and the Croatian-specific BERTić—using precision, recall, F1-score, and ROC-AUC. Results show that transformer-based models consistently outperform traditional approaches, with BERTić achieving the highest accuracy, reflecting its advantage as a language-specific model. The study demonstrates that AI can effectively support fact-checking by pre-screening economic content and flagging high-risk items for human review. However, limitations include reliance on translated datasets, reduced performance on complex categories such as satire and pseudoscience, and challenges in generalizing to real-time Croatian media. These findings underscore the need for native datasets, hybrid human-AI workflows, and governance aligned with the EU AI Act.
Keywords: disinformation; fake news; artificial intelligence; machine learning; language models (search for similar items in EconPapers)
JEL-codes: C6 F3 G O3 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jfinte:v:4:y:2025:i:4:p:60-:d:1785252
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