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Entropy and Information in Networks, from Societies to Cities

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".

Deadline for manuscript submissions: closed (30 September 2019) | Viewed by 20890

Special Issue Editors


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Guest Editor
Department of Applied Science and Technology, Polytechnic University of Turin, 10129 Turin, Italy
Interests: general physics and mathematics; optics; software; image processing applied to microscopy and satellite imagery
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Urbanism, Universidade Federal Fluminense, Rua Passo da Patria 156, Niteroi, Rio de Janeiro 24210-240, Brazil
Interests: urban studies; cities; society; social theory; sociology

Special Issue Information

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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Keywords

  • Shannon entropy
  • generalized entropies
  • social entropy
  • Tsallis entropy
  • order and disorder
  • systems theory
  • social networks
  • cities
  • environmental information
  • decision theory
  • ecology

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Published Papers (5 papers)

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Research

16 pages, 1767 KiB  
Article
(Neg)Entropic Scenarios Affecting the Wicked Design Spaces of Knowledge Management Systems
by Ulrich Schmitt
Entropy 2020, 22(2), 169; https://doi.org/10.3390/e22020169 - 1 Feb 2020
Cited by 8 | Viewed by 3388
Abstract
The envisioned embracing of thriving knowledge societies is increasingly compromised by threatening perceptions of information overload, attention poverty, opportunity divides, and career fears. This paper traces the roots of these symptoms back to causes of information entropy and structural holes, invisible private and [...] Read more.
The envisioned embracing of thriving knowledge societies is increasingly compromised by threatening perceptions of information overload, attention poverty, opportunity divides, and career fears. This paper traces the roots of these symptoms back to causes of information entropy and structural holes, invisible private and undiscoverable public knowledge which characterize the sad state of our current knowledge management and creation practices. As part of an ongoing design science research and prototyping project, the article’s (neg)entropic perspectives complement a succession of prior multi-disciplinary publications. Looking forward, it proposes a novel decentralized generative knowledge management approach that prioritizes the capacity development of autonomous individual knowledge workers not at the expense of traditional organizational knowledge management systems but as a viable means to foster their fruitful co-evolution. The article, thus, informs relevant stakeholders about the current unsustainable status quo inhibiting knowledge workers; it presents viable remedial options (as a prerequisite for creating the respective future generative Knowledge Management (KM) reality) to afford a sustainable solution with the generative potential to evolve into a prospective general-purpose technology. Full article
(This article belongs to the Special Issue Entropy and Information in Networks, from Societies to Cities)
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35 pages, 8632 KiB  
Article
An Entropy-Based Design Evaluation Model for Architectural Competitions through Multiple Factors
by Orkan Zeynel Güzelci and Sinan Mert Şener
Entropy 2019, 21(11), 1064; https://doi.org/10.3390/e21111064 - 30 Oct 2019
Cited by 6 | Viewed by 5184
Abstract
Generally, the evaluations in architectural competitions are based on quality where many criteria are involved. Additionally, many other inter-related criteria, identified by the members of the jury, emerge during jury evaluation. Hence, a great number of criteria play a role, with varying degrees [...] Read more.
Generally, the evaluations in architectural competitions are based on quality where many criteria are involved. Additionally, many other inter-related criteria, identified by the members of the jury, emerge during jury evaluation. Hence, a great number of criteria play a role, with varying degrees of importance, in the evaluation process. The order of importance and weights of criteria (factors) in the evaluation phases are not fixed and differ according to the approaches of the jury members. The objective of this study is to investigate whether subjective means of evaluation can be associated with an objective and computable evaluation model. Entropy, an objective method used to measure disorder in buildings, offers significant potential in enhancing the comprehensibility of subjective tendencies in jury evaluation of architectural competitions. Previous studies have identified an inverted U relationship between entropy and subjective responses based on single and multiple factors. The Entropy-Based Design Evaluation Model (EBDEM), a method, analyzes the level of objectivity in jury evaluation and questions the predictability of evaluations through examining the relationship between the entropy values of projects and success outcomes. The Weighted Overall Entropy (WOE) was obtained by multiplying multiple factor entropy values with different weight coefficients with the purpose of ranking each project on an inverted U graph similar to jury results. The relationship between WOE values calculated and the ranking of the projects in the competitions were investigated. The findings within this study indicate that there are no relationships between single factor entropy values and ranking of the projects. Additionally, it was found that WOE values calculated for single-competition compared to multiple-competitions were more similar to jury evaluation results. Full article
(This article belongs to the Special Issue Entropy and Information in Networks, from Societies to Cities)
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10 pages, 690 KiB  
Article
Investigating the Randomness of Passengers’ Seating Behavior in Suburban Trains
by Jakob Schöttl, Michael J. Seitz and Gerta Köster
Entropy 2019, 21(6), 600; https://doi.org/10.3390/e21060600 - 17 Jun 2019
Cited by 6 | Viewed by 3771
Abstract
In pedestrian dynamics, individual-based models serve to simulate the behavior of crowds so that evacuation times and crowd densities can be estimated or the efficiency of public transportation optimized. Often, train systems are investigated where seat choice may have a great impact on [...] Read more.
In pedestrian dynamics, individual-based models serve to simulate the behavior of crowds so that evacuation times and crowd densities can be estimated or the efficiency of public transportation optimized. Often, train systems are investigated where seat choice may have a great impact on capacity utilization, especially when passengers get in each other’s way. Therefore, it is useful to reproduce passengers’ behavior inside trains. However, there is surprisingly little research on the subject. Do passengers distribute evenly as it is most often assumed in simulation models and as one would expect from a system that obeys the laws of thermodynamics? Conversely, is there a higher degree of order? To answer these questions, we collect data on seating behavior in Munich’s suburban trains and analyze it. Clear preferences are revealed that contradict the former assumption of a uniform distribution. We subsequently introduce a model that matches the probability distributions we observed. We demonstrate the applicability of our model and present a qualitative validation with a simulation example. The model’s implementation is part of the free and open-source Vadere simulation framework for pedestrian dynamics and thus available for further studies. The model can be used as one component in larger systems for the simulation of public transport. Full article
(This article belongs to the Special Issue Entropy and Information in Networks, from Societies to Cities)
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17 pages, 485 KiB  
Article
Bipartite Structures in Social Networks: Traditional versus Entropy-Driven Analyses
by Wilhelm Rödder, Andreas Dellnitz, Friedhelm Kulmann, Sebastian Litzinger and Elmar Reucher
Entropy 2019, 21(3), 277; https://doi.org/10.3390/e21030277 - 13 Mar 2019
Cited by 6 | Viewed by 4063
Abstract
A special type of social networks is the so-called affiliation network, consisting of two modes of vertices: actors and events. Up to now, in the undirected case, the closeness of actors in such networks has been measured by their jointly-attended events. Indirect contacts [...] Read more.
A special type of social networks is the so-called affiliation network, consisting of two modes of vertices: actors and events. Up to now, in the undirected case, the closeness of actors in such networks has been measured by their jointly-attended events. Indirect contacts and attenuated and directed links are of minor interest in affiliation networks. These flaws make a veritable estimation of, e.g., possible message transfers amongst actors questionable. In this contribution, first, we discuss these matters from a graph-theoretical point of view. Second, so as to avoid the identified weaknesses, we propose an up-and-coming entropy-based approach for modeling such networks in their generic structure, replacing directed (attenuated) links by conditionals: if-then. In this framework, the contribution of actors and events to a reliable message transfer from one actor to another—even via intermediaries—is then calculated applying the principle of maximum entropy. The usefulness of this new approach is demonstrated by the analysis of an affiliation network called “corporate directors”. Full article
(This article belongs to the Special Issue Entropy and Information in Networks, from Societies to Cities)
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26 pages, 737 KiB  
Article
Matching Users’ Preference under Target Revenue Constraints in Data Recommendation Systems
by Shanyun Liu, Yunquan Dong, Pingyi Fan, Rui She and Shuo Wan
Entropy 2019, 21(2), 205; https://doi.org/10.3390/e21020205 - 21 Feb 2019
Cited by 5 | Viewed by 3712
Abstract
This paper focuses on the problem of finding a particular data recommendation strategy based on the user preference and a system expected revenue. To this end, we formulate this problem as an optimization by designing the recommendation mechanism as close to the user [...] Read more.
This paper focuses on the problem of finding a particular data recommendation strategy based on the user preference and a system expected revenue. To this end, we formulate this problem as an optimization by designing the recommendation mechanism as close to the user behavior as possible with a certain revenue constraint. In fact, the optimal recommendation distribution is the one that is the closest to the utility distribution in the sense of relative entropy and satisfies expected revenue. We show that the optimal recommendation distribution follows the same form as the message importance measure (MIM) if the target revenue is reasonable, i.e., neither too small nor too large. Therefore, the optimal recommendation distribution can be regarded as the normalized MIM, where the parameter, called importance coefficient, presents the concern of the system and switches the attention of the system over data sets with different occurring probability. By adjusting the importance coefficient, our MIM based framework of data recommendation can then be applied to systems with various system requirements and data distributions. Therefore, the obtained results illustrate the physical meaning of MIM from the data recommendation perspective and validate the rationality of MIM in one aspect. Full article
(This article belongs to the Special Issue Entropy and Information in Networks, from Societies to Cities)
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