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Some Observations on Fact-Checking Work with Implications for Computational Support

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arxiv 2305.02224 v4 pith:TI2DP2I6 submitted 2023-05-03 cs.HC

classification cs.HC
keywords fact-checkingcomputationalmembersworkcurrentlydifferentimplicationsorganisations
verification ladder T0 review T1 audit T2 compute T3 formal

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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.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 2 citations worldwide. Full citation record

  1. Civil Society in the Loop: Feedback-Driven Adaptation of (L)LM-Assisted Classification in an Open-Source Telegram Monitoring Tool

    cs.HC 2025-07 conditional novelty 4.0 of 10

    A design proposal for an open-source Telegram monitoring tool that lets civil society users correct AI classification labels, with the corrections used to retrain or reprompt the model.

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