Though concerns about the use of misinformation are certainly not new, the reach, speed and volume of misinformation in the digital era have generated a heightened sense of urgency among policymakers, scholars and the public alike. At the same time, relatively little is known about how such information is processed by people online – where much of it is encountered incidentally by citizens who are otherwise inattentive to public affairs – nor about its lasting effects on those who encounter it. This project therefore aims to develop a better understanding of the extent and impact of both quality and false, or misleading, information in online political news.
The project is interdisciplinary in nature, combining theory and methodology from the social sciences, humanities and computer science. It builds a strong conceptual foundation on normative and empirical theories of news quality that are found in journalism and media studies, as well as political communication research.
It draws on a variety of theories from social and cognitive psychology, plus communication, political and information sciences in its exploration of the effects of exposure to online news reporting. The project’s methodological approaches bring together insights from communication science and natural language processing.
The project’s aims are threefold. In a first step, it seeks to build automatic classifiers for signals of news quality. Recognising that the quality of reporting can vary from one story to the next – even within the same media outlet – this project will assess the quality of reporting at the article level.
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