Special Issue "Information Theory for Human and Social Processes"

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

Deadline for manuscript submissions: 30 June 2020.

Special Issue Editor

Prof. Martin Hilbert
Website
Guest Editor
Department of Communication, GG Computer Science, University of California, 370 Kerr Hall, 1 Shields Avenue, Davis, CA 95616, USA
Interests: computational social science; digitalization; algorithmification; complex social systems; international development; United Nations; computational mechanics; social change; mathematical theory of communication

Special Issue Information

Dear Colleagues,

Shannon famously applied his “mathematical theory of communication” to human communication, allegedly having his wife, Betty, estimating word probabilities to calculate the first approximation of the entropy of English. The following decades have seen creative further applications to humans and social processes (e.g., Miller, 1956; Attneave, 1959; Coleman, 1975; Ellis and Fisher, 1975; Cappella, 1979). These efforts lost steam in the 1980s, mainly because of the lack of adequate data, and limited computational power. Both limitations do not apply anymore. The increase in human interactions taking place in digital environments has led to an abundance of behavioral “big data”, enough even to calculate measures that converge rather slowly.

This Special Issue compiles creative research on the innovative uses of information theory, and its extensions, to better understand human behavior and social processes. Among other topics, the focus is set on human communication, social organization, social algorithms, human–machine interaction, artificial and human intelligence, collaborative teamwork, social media dynamics, information societies, digital development, and cognitive and machine biases—all online and/or offline.

Prof. Martin Hilbert
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • social science
  • behavioral science
  • human dynamics
  • human communication
  • social algorithms
  • human–machine interaction
  • social media
  • economics, sociology
  • antropology
  • political science
  • social psychology
  • social change

Published Papers (4 papers)

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Research

Open AccessArticle
Spatial-Temporal Characteristic Analysis of Ethnic Toponyms Based on Spatial Information Entropy at the Rural Level in Northeast China
Entropy 2020, 22(4), 393; https://doi.org/10.3390/e22040393 - 30 Mar 2020
Abstract
As a symbol language, toponyms have inherited the unique local historical culture in the long process of historical development. As the birthplace of Manchu, there are many toponyms originated from multi-ethnic groups (e.g., Manchu, Mongol, Korean, Hui, and Xibe) in Northeast China which [...] Read more.
As a symbol language, toponyms have inherited the unique local historical culture in the long process of historical development. As the birthplace of Manchu, there are many toponyms originated from multi-ethnic groups (e.g., Manchu, Mongol, Korean, Hui, and Xibe) in Northeast China which possess unique cultural connotations. This study aimed to (1) establish a spatial-temporal database of toponyms in Northeast China using a multi-source data set, and identify their ethnic types and origin times; and (2) explore the geographical distribution characteristics of ethnic toponyms and the evolution of rural settlements by comparing the spatial analysis and spatial information entropy methods. The results found that toponyms reflect not only the spatial distribution characteristics of the density and direction of ethnic groups, but also the migration law of rural settlements. Results also confirm that toponyms contain unique cultural connotations and provide a theoretical basis for the protection and promotion of the cultural connotations of toponyms. This research provides an entropic perspective and method for exploring the spatial-temporal evolutionary characteristics of ethnic groups and toponym mapping. Full article
(This article belongs to the Special Issue Information Theory for Human and Social Processes)
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Open AccessArticle
Entropy as a Measure of Attractiveness and Socioeconomic Complexity in Rio de Janeiro Metropolitan Area
Entropy 2020, 22(3), 368; https://doi.org/10.3390/e22030368 - 23 Mar 2020
Abstract
Defining and measuring spatial inequalities across the urban environment remains a complex and elusive task which has been facilitated by the increasing availability of large geolocated databases. In this study, we rely on a mobile phone dataset and an entropy-based metric to measure [...] Read more.
Defining and measuring spatial inequalities across the urban environment remains a complex and elusive task which has been facilitated by the increasing availability of large geolocated databases. In this study, we rely on a mobile phone dataset and an entropy-based metric to measure the attractiveness of a location in the Rio de Janeiro Metropolitan Area (Brazil) as the diversity of visitors’ location of residence. The results show that the attractiveness of a given location measured by entropy is an important descriptor of the socioeconomic status of the location, and can thus be used as a proxy for complex socioeconomic indicators. Full article
(This article belongs to the Special Issue Information Theory for Human and Social Processes)
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Open AccessArticle
The Emergence of Integrated Information, Complexity, and ‘Consciousness’ at Criticality
Entropy 2020, 22(3), 339; https://doi.org/10.3390/e22030339 - 16 Mar 2020
Abstract
Integrated Information Theory (IIT) posits that integrated information ( Φ ) represents the quantity of a conscious experience. Here, the generalized Ising model was used to calculate Φ as a function of temperature in toy models of fully connected neural networks. A Monte–Carlo [...] Read more.
Integrated Information Theory (IIT) posits that integrated information ( Φ ) represents the quantity of a conscious experience. Here, the generalized Ising model was used to calculate Φ as a function of temperature in toy models of fully connected neural networks. A Monte–Carlo simulation was run on 159 normalized, random, positively weighted networks analogous to small five-node excitatory neural network motifs. Integrated information generated by this sample of small Ising models was measured across model parameter spaces. It was observed that integrated information, as an order parameter, underwent a phase transition at the critical point in the model. This critical point was demarcated by the peak of the generalized susceptibility (or variance in configuration due to temperature) of integrated information. At this critical point, integrated information was maximally receptive and responsive to perturbations of its own states. The results of this study provide evidence that Φ can capture integrated information in an empirical dataset, and display critical behavior acting as an order parameter from the generalized Ising model. Full article
(This article belongs to the Special Issue Information Theory for Human and Social Processes)
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Open AccessArticle
Using the Maximal Entropy Modeling Approach to Analyze the Evolution of Sedentary Agricultural Societies in Northeast China
Entropy 2020, 22(3), 307; https://doi.org/10.3390/e22030307 - 09 Mar 2020
Abstract
The emergence of agriculture and the evolution of sedentary societies are among the most important processes in human history. However, although archeologists and social scientists have long been studying these processes, our understanding of them is still limited. This article focuses on the [...] Read more.
The emergence of agriculture and the evolution of sedentary societies are among the most important processes in human history. However, although archeologists and social scientists have long been studying these processes, our understanding of them is still limited. This article focuses on the Fuxin area in present-day Liaoning province in Northeast China. A systematic archeological survey we conducted in Fuxin in recent years located sites from five successive stages of the evolution of agricultural sedentary society. We used the principles of Maximal Entropy to study changes in settlement patterns during a long-term local trajectory, from the incipient steps toward a sedentary agricultural way of life to the emergence of complex societies. Based on the detailed data collected in the field, we developed a geo-statistical model based on Maximal Entropy (MaxEnt) that characterizes the locational choices of societies during different periods. This combination of high-resolution information on the location and density of archeological remains, along with a maximal entropy-based statistical model, enabled us to chart the long-term trajectory of the interactions between human societies and their natural environment and to better understand the different stages of the transition to developed sedentary agricultural society. Full article
(This article belongs to the Special Issue Information Theory for Human and Social Processes)
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