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README.md

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 license: apache-2.0
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+Model Details
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+Developed by: Faculty of Economics and Business, University of Rijeka
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+Funding: National Recovery and Resilience Plan, University of Rijeka (Grant No. uniri-mladi-drustv-23-52)
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+Models included: FastText, NBSVM, BiGRU, BERT, DistilBERT, BERTić (fine-tuned on Croatian-translated datasets)
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+Languages: Croatian (hr)
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+Intended domain: Economic news and disinformation detection
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+Intended Use
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+These models are released for research and educational purposes. They are designed to support the detection of economic disinformation in Croatian-language texts and should be used to:
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+Benchmark model performance across architectures.
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+Explore methods of adapting multilingual and regional models for specialized domains.
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+Support further academic research on fake news detection, economic disinformation, and AI ethics.
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+Limitations
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+Translation bias: The datasets were translated from English to Croatian. While validated by bilingual experts, subtle semantic shifts may affect results.
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+Annotation consistency: Original labels were preserved, but cultural and contextual interpretation in Croatian media may differ.
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+Generalizability: Models trained on specific corpora may not perform equally well on real-world, evolving disinformation patterns.
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+Resource demands: Transformer-based models (BERT, BERTić) require more computational resources compared to lighter models.
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+Ethical Considerations
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+Bias risks: Users should be aware that linguistic and cultural nuances may introduce bias into classification outcomes.
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+Potential misuse: These models could be misapplied for surveillance, censorship, or discrediting legitimate journalism. They are not intended for such purposes.
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+Responsible AI: Use of the models should follow principles of transparency, fairness, and accountability, in line with the EU AI Act.
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+Recommendations
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+Use the models only in non-commercial, academic, or public-good contexts.
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+Validate results with human expertise, especially in sensitive applications.
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+Cite this work when using the models in research outputs.
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+Report any observed errors, biases, or misuse to the maintainers.
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+Citation
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+If you use these models, please cite the associated paper:
+Buterin, V., Čišić, D., & Gržeta, I. (2025). Combating Economic Disinformation with AI: Insights from the EkonInfoChecker Project.