Some Observations on Fact-Checking Work with Implications for Computational Support (2305.02224v4)
Abstract: Social media and user-generated content (UGC) have become increasingly important features of journalistic work in a number of different ways. However, the growth of misinformation means that news organisations have had devote more and more resources to determining its veracity and to publishing corrections if it is found to be misleading. In this work, we present the results of interviews with eight members of fact-checking teams from two organisations. Team members described their fact-checking processes and the challenges they currently face in completing a fact-check in a robust and timely way. The former reveals, inter alia, significant differences in fact-checking practices and the role played by collaboration between team members. We conclude with a discussion of the implications for the development and application of computational tools, including where computational tool support is currently lacking and the importance of being able to accommodate different fact-checking practices.
- QMUL-SDS at CheckThat! 2021: Enriching Pre-Trained Language Models for the Estimation of Check-Worthiness of Arabic Tweets. In CLEF (Working Notes).
- Natural Language Inference with Self-Attention for Veracity Assessment of Pandemic Claims. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 1496–1511.
- Machine Learning for Mediation in Armed Conflicts. arXiv preprint arXiv:2108.11942.
- Knowledge Work in Platform Fact-Checking Partnerships. International Journal of Communication, 17: 21.
- Grounded theory method in information systems research: its nature, diversity and opportunities. European Journal of Information Systems, 22(1): 1–8.
- Bittner, E. 1965. The concept of organization. Social research, 239–255.
- Workshop on Rumors and Deception in Social Media: Detection, Tracking, and Visualization. In Proceedings of the 24th International Conference on World Wide Web.
- Emerging journalistic verification practices concerning social media. Journalism practice, 10(3): 323–342.
- The state of human-centered NLP technology for fact-checking. Information Processing & Management, 60(2): 103219.
- Human-in-the-loop Artificial Intelligence for Fighting Online Misinformation: Challenges and Opportunities. IEEE Data Eng. Bull., 43(3): 65–74.
- Diseases, T. L. I. 2020. The COVID-19 infodemic. The Lancet. Infectious Diseases, 20(8): 875.
- PHEMEPlus: Enriching Social Media Rumour Verification with External Evidence. In Proceedings of the Fifth Fact Extraction and VERification Workshop (FEVER), 49–58.
- Learning Disentangled Latent Topics for Twitter Rumour Veracity Classification. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 3902–3908. Online: Association for Computational Linguistics.
- The rise of fact-checking sites in Europe. Technical report, Reuters Institute for the Study of Journalism.
- A survey on automated fact-checking. Transactions of the Association for Computational Linguistics, 10: 178–206.
- Human and technological infrastructures of fact-checking. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2): 1–36.
- Evaluating the generalisability of neural rumour verification models. Information Processing & Management, 60(1): 103116.
- ProoFVer: Natural Logic Theorem Proving for Fact Verification. TACL, 10: 1013–1030.
- Using nlp for fact checking: A survey. Designs, 5(3): 42.
- True or false: Studying the work practices of professional fact-checkers. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW1): 1–44.
- Automated fact-checking for assisting human fact-checkers. arXiv preprint arXiv:2103.07769.
- Holding AI to Account: Challenges for the Delivery of Trustworthy AI in Healthcare. ACM Transactions on Computer-Human Interaction.
- Ethnomethodology at work. Routledge.
- Rubin, V. L. 2022. Content verification for social media: From deception detection to automated fact-checking. The SAGE handbook of social media research methods.
- Topic-Aware Evidence Reasoning and Stance-Aware Aggregation for Fact Verification. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 1612–1622.
- Slota, S. C. 2020. Designing Across Distributed Agency: Values, participatory design and building socially responsible AI. Good Systems-Published Research.
- Supporting the use of user generated content in journalistic practice. In Proceedings of the 2017 ACM CHI conference on Human Factors in Computing Systems, 3632–3644.
- Wolf, C. T. 2020. AI models and their worlds: Investigating data-driven, AI/ML ecosystems through a work practices lens. In Sustainable Digital Communities: 15th International Conference, iConference 2020, Boras, Sweden, March 23–26, 2020, Proceedings 15, 651–664. Springer.
- Automated fact-checking: A survey. Language and Linguistics Compass, 15(10): e12438.
- Supervised contrastive learning for multimodal unreliable news detection in covid-19 pandemic. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 3637–3641.
- NewsQuote: A Dataset Build on Quote Extraction and Attribution for Expert Recommendation. In Proceedings of the International AAAI Conference on Web and Social Media. AAAI Press.
- PANACEA: An Automated Misinformation Detection System on COVID-19. arXiv preprint arXiv:2303.01241.
- Disentangled Learning of Stance and Aspect Topics for Vaccine Attitude Detection in Social Media. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 1566–1580.
- Rob Procter (44 papers)
- Miguel Arana-Catania (13 papers)
- Yulan He (113 papers)
- Maria Liakata (59 papers)
- Arkaitz Zubiaga (88 papers)
- Elena Kochkina (19 papers)
- Runcong Zhao (13 papers)