Slavic NLP 2027

Disinformation Detection

Binary classification of texts as disinformation vs. non-disinformation.

Task Overview

Binary classification of texts as disinformation vs. non-disinformation, covering Polish, Slovak and Russian (to be extended), building on existing resources such as MIPD for Polish. English-language data (MultiDis, MALINT) is also included to encourage broader participation. Co-organized with NASK National Research Institute, a leading Polish institution involved in monitoring and countering disinformation.

Data & Resources

Training Data. Participants may use any relevant public or private disinformation and misinformation datasets they consider useful for developing their systems, and they are encouraged to explore additional resources beyond the ones listed below when appropriate.

The task builds on several publicly available datasets and benchmark resources for disinformation detection. These datasets were introduced in papers presented at major ACL venues, including EMNLP, ACL, and EACL, and they are directly relevant to the current task because they cover disinformation detection and datasets.

Test Data. Test data will be released via this website in December. It will be available in Polish, Russian, Slovak and English.

Papers to Cite in Your Paper Describing Your System

As this shared task builds upon existing and published studies and datasets, please cite the papers mentioned below in your paper describing your system.

MIPD: Exploring Manipulation and Intention in a Novel Corpus of Polish Disinformation

ACL Anthology 
@inproceedings{modzelewski-etal-2024-mipd,
    title = "{MIPD}: Exploring Manipulation and Intention In a Novel Corpus of {P}olish Disinformation",
    author = "Modzelewski, Arkadiusz  and
      Da San Martino, Giovanni  and
      Savov, Pavel  and
      Wilczy{\'n}ska, Magdalena Anna  and
      Wierzbicki, Adam",
    booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.emnlp-main.1103/",
    doi = "10.18653/v1/2024.emnlp-main.1103",
}

MALINT: Malicious Intent Dataset and Inoculating LLMs for Enhanced Disinformation Detection

ACL Anthology 
@inproceedings{modzelewski-etal-2026-malicious,
    title = "{MAL}icious {INT}ent Dataset and Inoculating {LLM}s for Enhanced Disinformation Detection",
    author = "Modzelewski, Arkadiusz  and
      Sosnowski, Witold  and
      Papadopulos, Eleni  and
      Sartori, Elisa  and
      Labruna, Tiziano  and
      Da San Martino, Giovanni  and
      Wierzbicki, Adam",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.eacl-long.144/",
    doi = "10.18653/v1/2026.eacl-long.144",
    pages = "3125--3148",
    ISBN = "979-8-89176-380-7"
}

PCoT: Persuasion-Augmented Chain of Thought for Detecting Fake News and Social Media Disinformation

ACL Anthology 
@inproceedings{modzelewski-etal-2025-pcot,
    title = "{PC}o{T}: Persuasion-Augmented Chain of Thought for Detecting Fake News and Social Media Disinformation",
    author = "Modzelewski, Arkadiusz  and
      Sosnowski, Witold  and
      Labruna, Tiziano  and
      Wierzbicki, Adam  and
      Da San Martino, Giovanni",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.acl-long.1215/",
    doi = "10.18653/v1/2025.acl-long.1215",
    pages = "24959--24983",
    ISBN = "979-8-89176-251-0"
}

Task Contact

Arkadiusz Modzelewski — contact@amodzelewski.com

See the Call for Participation page for submission guidelines.