Mass media, the ‘sensational message’, and metamorphic truths Alvin Vista ⇑ University of Melbourne, 100 Leicester Street, Parkville, Melbourne, VIC, Australia article info Article history: Available online 27 June 2014 Keywords: Mass media Perception Psychology Technology Viral phenomena Pervasive computing Consumer behavior Epistemology Information and power abstract The purpose of this paper is to discuss the effects of mass media’s ability to rapidly spread sensational messages. With the view that the accuracy or truth of the ‘sensational message’ can change, either evolving naturally within our collective perception or through more deliberate ways, this then presents some scenarios in which ever more flexible notions of truth in the future may provide not only challenges but also opportunities. Using differ- ent perspectives but always with a bit of lightheartedness, two events that are separated by half a century and a vast expanse of technological advances are presented as lenses with which to examine our collective obsession of the sensational and how this obsession may influence our perspective as well as our subsequent choices. Looking towards the increasingly connected future, the challenges and economic implications of our suscepti- bility to sensational media are explored so that in the end, the readers will have gained insights on mass media’s power to flex our notions of truth. Ó 2014 Elsevier Ltd. All rights reserved. 1. Prelude Rumors and viruses are close cousins, at least from the point of view of network scientists. Epidemic spreading in networks is an area of study that is increasingly becoming important in the age of exponentially increasing connectivity, and analogies between real-world epidemics and virtual epidemics have been the focus of several studies (e.g., Boman and Johansson, 2007; Gewin, 2004). But whereas epidemics caused by biological (or digital) viruses spread without the conscious effort of infected individuals, the spread of viral media is largely due to conscious choice by the participants – akin to having been infected with a cold and the symptoms include wanting to sneeze on someone. There are additional impor- tant differences between real-world and virtual epidemics (see Boman & Johansson, 2007). For example, statistical modeling on the spread of viral media has shown distinct differences in the dynamics of spreading between different types of networks (see Pastor-Satorras and Vespignani, 2001; Moreno et al., 2004; Nekovee et al., 2007). In particular, within scale-free networks 1 there is no limiting threshold below which an ‘infection’ gets stifled and fails to spread exponentially (Pastor-Satorras and Vespignani, 2001, p. 3201). Moreover, the rate of spread in proportion to the size of the network is faster compared to random networks (Nekovee et al., 2007, pp. 467–468) 2 . These characteristics have important implications http://dx.doi.org/10.1016/j.tele.2014.05.005 0736-5853/Ó 2014 Elsevier Ltd. All rights reserved. ⇑ Tel.: +61 41356 1957. E-mail address: vistaa@unimelb.edu.au 1 A scale-free network is a network with certain nodes having unusually large number of connections to other nodes and the distribution of the number of connections follows a power law. This can be contrasted with a random network where the number of connections is randomly distributed. For those interested in a deeper and more technical exploration of these networks see seminal works by Albert and Barabási (2002), Barabási and Albert (1999) and Barabási and Bonabeau (2003) for scale-free networks, and Erd} os and Rényi (1959, 1960) for random networks. 2 This is primarily because as the network size increases, the rate of spread becomes faster in scale-free networks due to the effect of hubs shortening the mean distance between any two members within the network (Pastor-Satorras and Vespignani, 2001, pp. 3201–3202). Telematics and Informatics 32 (2015) 416–423 Contents lists available at ScienceDirect Telematics and Informatics journal homepage: www.elsevier.com/locate/tele