Social Interaction and the City: The Effect of Space on the Reduction of Entropy

Netto, Vinícius M.; Meirelles, João; Ribeiro, Fabiano L.

doi:10.1155/2017/6182503

Cited by 24 publications

(19 citation statements)

References 46 publications

(58 reference statements)

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“…One way to do this is quantifying the amount of environmental information available for agents in their decisions. We tested that idea through an “enaction model” able to assess information 3 proposed in a companion article (Netto et al [ 88 ]). Like situation semantics, our model considers agents, types of action, spatial and temporal locations, situations (represented by activity places) and parameters able to capture aspects of the agent’s cognitive behaviour, namely the ability to track and recognize social situations, make decisions based on their individual orientations, and change their own actions and the semantic environment.…”

Section: Information 3 (Enacted)mentioning

confidence: 99%

Cities, from Information to Interaction

Netto

Brigatti

Meirelles

et al. 2018

Entropy

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From physics to the social sciences, information is now seen as a fundamental component of reality. However, a form of information seems still underestimated, perhaps precisely because it is so pervasive that we take it for granted: the information encoded in the very environment we live in. We still do not fully understand how information takes the form of cities, and how our minds deal with it in order to learn about the world, make daily decisions, and take part in the complex system of interactions we create as we live together. This paper addresses three related problems that need to be solved if we are to understand the role of environmental information: (1) the physical problem: how can we preserve information in the built environment? (2) The semantic problem: how do we make environmental information meaningful? and (3) the pragmatic problem: how do we use environmental information in our daily lives? Attempting to devise a solution to these problems, we introduce a three-layered model of information in cities, namely environmental information in physical space, environmental information in semantic space, and the information enacted by interacting agents. We propose forms of estimating entropy in these different layers, and apply these measures to emblematic urban cases and simulated scenarios. Our results suggest that ordered spatial structures and diverse land use patterns encode information, and that aspects of physical and semantic information affect coordination in interaction systems.

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Section: Information 3 (Enacted)mentioning

confidence: 99%

Cities, from Information to Interaction

Netto

Brigatti

Meirelles

et al. 2018

Entropy

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“…In this paper we are interested in the effect of two different kinds of relevant complex networks in finance [1][2][3] on implied cost of capital for the listed companies, particularly in a prominent emerging market, Brazil, which have been the subject of studies on complexity in other disciplines such as epidemiology [4], geophysics [5], ecology [6,7], and information science [8,9].…”

Section: Introductionmentioning

confidence: 99%

The Complexity of Social Capital: The Influence of Board and Ownership Interlocks on Implied Cost of Capital in an Emerging Market

2018

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Starting from sociological perspectives on complexity, we show how the social capital of boards and owners networks affects the implied cost of capital of companies listed on Brazilian stock exchange. We specifically show arguments and evidence that the effect of the relational resources found in the direct, indirect, and heterogeneous board's ties reduces the cost of capital while relational resources embedded in shareholder networks increase the cost of capital. Our results show that while the increase in the relational resources of the board reduces the implied cost of capital, an increase in these shared resources in the ownership relationships of the firm increases the cost of financial capital.

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“…Social interaction explores a particular concept of “social entropy” or how social systems deal with uncertainty and unpredictability in the transition from individual actions to systems of interaction. Simulation studies suggest that states and fluctuations of entropy are a vital part of social reproduction and reveal a deep connection between social, informational, and spatial systems (Netto et al., ). Similarly, entropy has been measured not just spatially but across groups to study diversity, racial segregation, and political polarization, which are inextricably linked in urban environments.…”

Section: Uncertainty Measurement In Economic Disparitymentioning

confidence: 99%

Shannon Entropy for Quantifying Uncertainty and Risk in Economic Disparity

Mishra¹,

Ayyub

2019

Risk Analysis

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The rise in economic disparity presents significant risks to global social order and the resilience of local communities. However, existing measurement science for economic disparity (e.g., the Gini coefficient) does not explicitly consider a probability distribution with information, deficiencies, and uncertainties associated with the underlying income distribution. This article introduces the quantification of Shannon entropy for income inequality across scales, including national-, subnational-, and city-level data. The probabilistic principles of Shannon entropy provide a new interpretation for uncertainty and risk related to economic disparity. Entropy and information-based conflict rise as world incomes converge. High-entropy instances can resemble both happy and prosperous societies as well as a socialist-communist social structure. Low entropy signals high-risk tipping points for anomaly and conflict detection with higher confidence. Finally, spatial-temporal entropy maps for U.S. cities offer a city risk profiling framework. The results show polarization of household incomes within and across Baltimore, Washington, DC, and San Francisco. Entropy produces reliable results at significantly reduced computational costs than Gini coefficients.

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Social Interaction and the City: The Effect of Space on the Reduction of Entropy

Cited by 24 publications

References 46 publications

Cities, from Information to Interaction

Cities, from Information to Interaction

The Complexity of Social Capital: The Influence of Board and Ownership Interlocks on Implied Cost of Capital in an Emerging Market

Shannon Entropy for Quantifying Uncertainty and Risk in Economic Disparity

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