Building an informing science model in light of fake news

Abstract

Many disciplines have addressed the issue of "fake news." This topic is of central concern to the transdiscipline of Informing Science, which endeavors to understand all issues related to informing. This paper endeavors to build a model to address not only fake news but all informing and misin-forming. To do this, it explores how errors get into informing systems, the issue of bias, and the models previously created to explore the complexity of informing. That is, this paper examines mod-els and frameworks proposed to explore informing in the presence of bias, misinformation, disinfor-mation, and fake news from the perspective of Informing Science. It concludes by introducing a more nuanced model that considers some of the topics explored in the paper.