Aim and Topics

The aim of the Workshop is to generate a discussion on, and possibly provide countermeasures to, the problem of online information disorder, by identifying subjective and objective factors associated with information credibility and truthfulness respectively, and integrating such factors as fundamental dimensions of relevance within Information Retrieval Systems. Given that the problem in recent years has been addressed from various points of view (e.g., fake news detection, bot detection, information truthfulness assessment, etc.), the purpose of this Workshop proposed at ECIR 2025 is to consider these issues in the context of Information Retrieval, also considering related Artificial Intelligence fields such as Natural Language Processing (NLP), Natural Language Understanding (NLU), Computer Vision, Machine and Deep Learning.

The topics of interest include, but are not limited to, the following:

  • Access to and retrieval of truthful information
  • Bot/spam/troll detection
  • Computational fact-checking
  • Credibility assessment of online documents
  • Crowdsourcing for information truthfulness assessment
  • Disinformation/misinformation/bias detection
  • Evaluation strategies to assess information truthfulness
  • Generative models and information truthfulness assessment
  • Human-in-the-loop misinformation detection
  • Harassment/bullying/hate speech detection
  • Information polarization in online communities, filter bubbles, echo chambers
  • Propaganda identification/analysis
  • Retrieval of credible and truthful information
  • Security, privacy, and information truthfulness
  • Sentiment/emotional analysis/stance detection
  • Societal reaction to misinformation
  • Trust and reputation

Data-driven approaches, supported by publicly available datasets, are more than welcome.