Entropy and Information in Networks, from Societies to Cities

Dear Colleagues,

Among the first works that discussed and popularized the role of entropy in society, we can find the book “Entropy: A New World View” by Jeremy Rifkin and Ted Howard, published in 1980. Preceded by books such as those by Y. S. Touloukian (1956) and R. Arnheim (1974) on entropy in science, communication, and arts, the book by Rifkin and Howard used the law of entropy to analyze the world's economic and social structures. In the book, the authors linked entropy, viewed as disorder, to the behaviour of social systems wasting natural resources at a striking rate.

This idea is even more crucial if we think of the increasing challenges faced by contemporary urban societies. Indeed, societies are formed by large numbers of agents and networks, places, and technical objects performing in potentially different ways. Nevertheless, if any system is to reproduce itself, it has to evolve into states in which connections and coordination between such entities become possible. As Niklas Luhman’s (1995) work suggests, it is interaction and coordination that enable such diverse sets of agencies and networks to somehow emerge as a working system.

Challenges for a social system’s self-maintenance and reproduction may be clarified through a classic concept in information theory and thermodynamics: entropy, a measure of information in the face of uncertainty (Shannon, 1948), and a measure of disorder (Prigogine and Stengers, 1984; Hidalgo, 2015). After Shannon, this concept has been widely applied in many different fields and disciplines, from information theory and computer sciences to biology and financial studies. In one way or another, we face entropy all the time. Our daily actions are riddled with uncertainty, from daily choices we make to the way our actions play out once they merge into those of other people. If entropy relates to uncertainty and disorder, and if social systems face entropy all the time, continuity and self-maintenance become major issues. In this framework, entropy becomes key to understanding complex social systems, from daily decisions to emerging states, patterns, or even crises.

By the same token, from physics to the social sciences, information is now seen as a key component of reality. In particular, information in social networks and in urban environments is expected to have an increasing function. As we deal with information encoded in and decoded from the environment in order to make daily decisions and take part in complex interaction systems, cities might play a role in the social system’s ability to keep itself in certain entropy states (Netto et al, 2018). In short, aspects of environmental information might affect coordination in interaction systems.

As related subjects, entropy and information are now of interest to social theorists, urban theorists, physicists, and cognitive geographers alike and require reliable methods of analysis. We invite contributions to this Special Issue, which is devoted to the use of entropy and information in understanding different aspects of society, its environment and their future development.

Dr. Amelia Carolina Sparavigna
Dr. Vinicius M. Netto
Guest Editors

 

References

Arnheim, R. Entropy and art: An essay on disorder and order; University of California Press: Oakland, CA, USA, 1974.

Hidalgo, C. Why Information Grows: The Evolution of Order, from Atoms to Economies; Basic Books: New York, NY, USA, 2015.

Luhmann, N. Social Systems; Stanford University Press: Redwood City, CA, USA, 1995.

Netto, V.M.; Brigatti, E.; Meirelles, J.; Ribeiro, F.L.; Pace, B.; Cacholas, C.; Sanches, P. Cities, from Information to Interaction. Entropy 2018, 20, 834.

Prigogine, I.; Stengers, I. Order out of Chaos: Man’s New Dialogue with Nature; Bantam Books: New York, NY, USA, 1984.

Rifkin, J.; Howard, T. Entropy: A new world view; Viking Press, New York, NY USA, 1980.

Shannon, C.E. Communication theory of secrecy systems. Bell Syst. Tech. J. 1949, 28, 656–715.

Touloukian, Y.S. The Concept of Entropy in Communication, Living Organisms, and Thermodynamic; Purdue University, 1956.

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