Dataset development and curation

The design, collection, annotation, and release of datasets that support reproducible misinformation research. Key considerations include: ethical data governance, privacy protection, platform terms of service compliance, annotation quality and inter-rater agreement, dataset documentation and provenance, public-release strategies that balance research access with disclosure risk, and long-term sustainability of data sharing infrastructure.

Related topics

• Datasets and benchmarks — specific research datasets
• Dataset curation — focused on curation and maintenance
• Dataset quality — annotation quality and validation
• Computational social science and large-scale text analysis — methodological context