A Scoping Review of Fake News Detection Using Eye-Tracking Measures: A Preregistered Protocol

The proliferation of fake news has been a growing concern in the recent few years. Consumption of misinformation leads to negative social and individual outcomes, warranting the need for robust detection methods to prevent further dissemination and mitigate its impact across the public domain. While various detection methods have been developed across the years, using eye-tracking methods has recently gained increasing attention for assessing news veracity. Such metrics offer unique insights into the physiological processes involved in information evaluation and can address the limitations that traditional methods of detection possess. Yet, the potential of how eye-tracking measures can be used as a detection tool remains unclear, due to a lack of synthesized evidence and established methodologies employed in current research. A scoping review is proposed to qualitatively synthesise all currently available evidence of using eye-tracking metrics in fake news detection. Through a systematic approach guided by the PRISMA-ScR framework, key methodological and theoretical frameworks will be identified. Research gaps will also be elucidated to understand the current limitations of this field, paving the way for future investigators to refine and optimize current eye-tracking models and their applications in fake news detection. Findings from this review will also inform the future development of objective and real-time detection systems that integrate both physiological and cognitive markers for improved misinformation mitigation strategies.