Automated fact-checking (AFC) has grown in popularity to address the online spread of misinformation, propaganda, and misinformation about critical contemporary issues. Various natural language processing, machine learning, knowledge representation and database techniques have been used in AFC, whereas, from an end-user perspective, little attention was paid to the quality of the datasets feeding these information systems. Considering the recognised need to blend AI-based tools with journalistic values, this research proposes a practical framework for assessing and improving data quality when developing or implementing AFC systems. Drawing on an interdisciplinary approach, it contributes to understanding how to better align AI-based solutions with ethical standards in journalism and fact-checking.
The full paper is available here and here
