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 et al., 2018). However, this 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 consumption of data rely on a mixture of psychology, sociology, political science, economics, linguistics, marketing, and fine arts. The authors for this effort discuss deception’s history, both old and new, from an interdisciplinary viewpoint and then proceed to discuss how various disciplines contribute to aiding in the detection and countering of fake news narratives. A discussion of various fake news types (printed, staged events, altered photographs, and deep fakes) ensues with the various technologies being used to identify these; the shortcomings of those technologies and finally the insights offered by the other disciplines 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 put forth 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. (shrink)

Specific emotions and colors are associated. The current study tested whether the interference of colors with affective processing occurs solely in the semantic stage or extends to a more complex stage like the lexical processing of emotional words. We performed two experiments to determine the effect of colors on affective processing. In Experiment 1, participants completed a color-emotion priming task. The priming stimulus included a color-tinted image of a neutral face, followed by a target stimulus of gray-scaled emotional and neutral (...) faces after 50 ms. Experiment 2 used a modified emostroop paradigm and superimposed emotion words on the center of the color-tinted emotional and neutral faces. Results showed the priming effect of red for the angry face compared to the control, but not in blue for the sad face compared to the control. However, responses to the blue-sad pair were significantly faster than the red-sad pair. In the color-emostroop task, we observed a significant interaction between color and emotion target words in the modified emostroop task. Participants detected sad targets more accurately and faster in blue than red, but only in the incongruent condition. The results indicate that the influence of color in the processing of emotional information exists at the semantic level but found no evidence supporting the lexical level effect. (shrink)