Interdisciplinary Lessons Learned While Researching Fake News

The misleading and propagandistic tendencies in American news reporting have been a part of public discussion from its earliest days as a republic (Innis 2007; Sheppard 2007).‘Fake news’is hardly new (McKernon 1925) and the term has been applied to a variety of distinct phenomenon ranging from satire to news,which one may find disagreeable (Jankowski 2018; Tandoc, Lim, and Ling 2018).However, the problem has become increasingly acute in recent years with the Macquarie Dictionary declaring ‘fake news’ the word of the year in 2016 (Lavoipierre 2017). The international recognition of fake news as a problem (Pomerantsev and Weiss 2014; Applebaum and Lucas 2016) has led to a number of initiatives to mitigate perceived causes, with varying levels of success (Flanagin and Metzger, 2014; Horne and Adali 2017; Sample et al. 2018). The inability to create a holistic solution continues to stymie researchers and vested parties. A significant contributor to the problem is the interdisciplinary nature of digital deception. While technology enables the rapid and wide dissemination of digitally deceptive data, the design and consumptionof data relies on a mixture of psychology, sociology, political science, economics, linguistics, marketing, and fine arts. The authors of this paper discuss deception’s history, both old and new, from an interdisciplinary viewpoint, then proceed to discuss how various disciplines contribute to aiding in the detection and countering of Fake news narratives. The authors then provide a discussion of various fake news types (printed, staged events, altered photos and deep fakes), followed with the various technologies being used to identify these, an analysis of the shortcomings of these supporting technologies and finally the insights offered by the other disciplines that can be incorporated to improve outcomes. A three-point evaluation model that focuses on contextual data evaluation, pattern-spread and archival analysis of both the author and publication archives is introduced. While the model proposed cannot determine fact from fiction, the ability to measure distance from fact across various domains provides a starting point for evaluating the veracity of a new story. “If it is not true, it is very well invented” Giordano Bruno.