Trustworthiness, accuracy, and transparency: the audience's perceptions of errors in data journalism

Media publishers are increasingly turning to data-driven storytelling, or data journalism, as a means to restore trust by promising impartiality and transparency. However, the inherently human nature of data introduces errors and biases, emphasising the need to scrutinise the data production process. This study presents an illustrative case from the Brazilian newspaper Folha de S. Paulo, which published a data-driven story on expired COVID-19 vaccines. While the story gained significant attention, it contained inaccuracies and misconceptions, highlighting the challenges of data verification. The chapter delves into the audience’s perspective, examining how the public links human-made errors to misinformation and how normative journalistic values influence its perception of errors. With this aim, the study employs content analysis of audience commentaries on related news articles about the story. The dataset comprises 201 comments. The content analysis utilises a codebook developed from existing literature on trustworthiness, accuracy, and transparency. The study sheds light on the complex relationship between data journalism, trust, and audience perceptions, providing valuable insights for media practitioners and scholars alike.