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

TL;DR

This paper explores the practices and challenges of fact-checking in journalism through interviews, highlighting the need for adaptable computational tools to support diverse fact-checking methods amid rising misinformation.

Contribution

It provides qualitative insights into fact-checking workflows and discusses implications for developing flexible computational support tools.

Findings

Significant variation in fact-checking practices

Collaboration plays a key role in fact-checking processes

Current computational tools lack adaptability to diverse practices

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.