# Human and technological infrastructures of fact-checking

arXiv: https://arxiv.org/abs/2205.10894 · HTML: https://mlsanity.com/paper/2205.10894/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 May 2022.

## Built on by (most cited first, 16 of 16)

- [Scientific Fact-Checking: A Survey of Resources and Approaches](https://mlsanity.com/paper/2305.16859/) (2023)
- [Show Me the Work: Fact-Checkers' Requirements for Explainable Automated Fact-Checking](https://mlsanity.com/paper/2502.09083/) (2025)
- [Does Human Collaboration Enhance the Accuracy of Identifying LLM-Generated Deepfake Texts?](https://mlsanity.com/paper/2304.01002/) (2023)
- [The Impact and Opportunities of Generative AI in Fact-Checking](https://mlsanity.com/paper/2405.15985/) (2024)
- [Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AI](https://mlsanity.com/paper/2308.07213/) (2023)
- [Can Community Notes Replace Professional Fact-Checkers?](https://mlsanity.com/paper/2502.14132/) (2025)
- [Autonomation, Not Automation: Activities and Needs of European Fact-checkers as a Basis for Designing Human-Centered AI Systems](https://mlsanity.com/paper/2211.12143/) (2022)
- [Can LLMs Automate Fact-Checking Article Writing?](https://mlsanity.com/paper/2503.17684/) (2025)
- [The Implications of Open Generative Models in Human-Centered Data Science Work: A Case Study with Fact-Checking Organizations](https://mlsanity.com/paper/2408.01962/) (2024)
- [Decide less, communicate more: On the construct validity of end-to-end fact-checking in medicine](https://mlsanity.com/paper/2506.20876/) (2025)
- [Co-FactChecker: A Framework for Human-AI Collaborative Claim Verification Using Large Reasoning Models](https://mlsanity.com/paper/2604.13706/) (2026)
- [Graphical Models of False Information and Fact Checking Ecosystems](https://mlsanity.com/paper/2208.11582/) (2022)
- [Civil Society in the Loop: Feedback-Driven Adaptation of (L)LM-Assisted Classification in an Open-Source Telegram Monitoring Tool](https://mlsanity.com/paper/2507.06734/) (2025)
- [Towards Multi-Agent-Simulation-Based Community Note Evaluation](https://mlsanity.com/paper/2606.18268/) (2026)
- [Ctrl-F-Resist. Practices, Challenges, and Technical Needs of Civil Society Organizations Monitoring the Far-Right Online](https://mlsanity.com/paper/2609.00808/) (2026)
- [SoK: Formal Methods for Fact-Checking and Information Integrity](https://mlsanity.com/paper/2609.23239/) (2026)

## Abstract (arXiv)

Increasing demands for fact-checking has led to a growing interest in developing systems and tools to automate the fact-checking process. However, such systems are limited in practice because their system design often does not take into account how fact-checking is done in the real world and ignores the insights and needs of various stakeholder groups core to the fact-checking process. This paper unpacks the fact-checking process by revealing the infrastructures -- both human and technological -- that support and shape fact-checking work. We interviewed 26 participants belonging to 16 fact-checking teams and organizations with representation from 4 continents. Through these interviews, we describe the human infrastructure of fact-checking by identifying and presenting, in-depth, the roles of six primary stakeholder groups, 1) Editors, 2) External fact-checkers, 3) In-house fact-checkers, 4) Investigators and researchers, 5) Social media managers, and 6) Advocators. Our findings highlight that the fact-checking process is a collaborative effort among various stakeholder groups and associated technological and informational infrastructures. By rendering visibility to the infrastructures, we reveal how fact-checking has evolved to include both short-term claims centric and long-term advocacy centric fact-checking. Our work also identifies key social and technical needs and challenges faced by each stakeholder group. Based on our findings, we suggest that improving the quality of fact-checking requires systematic changes in the civic, informational, and technological contexts.