Social Interaction Scaling for Contact Networks

Urbanization drives the need for predictive and quantitative methods to understand city growth and adopt informed urban planning. Population increases trigger changes in city attributes that are explicable by scaling laws. These laws show superlinear scaling of communication with population size, as...

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Main Authors: Yusra Ghafoor, Yi-Shin Chen, Kuan-Ta Chen
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/11/9/2545
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spelling doaj-52f7c0db7fd6499e87d105cfe96a95c82020-11-25T00:52:41ZengMDPI AGSustainability2071-10502019-05-01119254510.3390/su11092545su11092545Social Interaction Scaling for Contact NetworksYusra Ghafoor0Yi-Shin Chen1Kuan-Ta Chen2Social Networks and Human-Centered Computing, Taiwan International Graduate Program, Academia Sinica, Taipei 115, TaiwanInstitute of Information Systems and Applications, Department of Computer Science, National Tsing Hua University, Hsinchu 300, TaiwanInstitute of Information Science, Academia Sinica, Taipei 115, TaiwanUrbanization drives the need for predictive and quantitative methods to understand city growth and adopt informed urban planning. Population increases trigger changes in city attributes that are explicable by scaling laws. These laws show superlinear scaling of communication with population size, asserting an increase in human interaction based on city size. However, it is not yet known if this is the case for social interaction among close contacts, that is, whether population growth influences connectivity in a close circle of social contacts that are dynamic and short-spanned. Following this, a network is configured, named <i>contact networks</i>, based on familiarity. We study the urban scaling property for three social connectivity parameters (degree, call frequency, and call volume) and analyze it at the collective level and the individual level for various cities around the world. The results show superlinear scaling of social interactions based on population for contact networks; however, the increase in level of connectivity is minimal relative to the general scenario. The statistical distributions analyze the impact of city size on close individual interactions. As a result, knowledge of the quantitative increase in social interaction with urbanization can help city planners in devising city plans, developing sustainable economic policies, and improving individuals&#8217; social and personal lives.https://www.mdpi.com/2071-1050/11/9/2545urban scalingsocial interactioncontact networkscommunicationindividual connectivitycity size
collection DOAJ
language English
format Article
sources DOAJ
author Yusra Ghafoor
Yi-Shin Chen
Kuan-Ta Chen
spellingShingle Yusra Ghafoor
Yi-Shin Chen
Kuan-Ta Chen
Social Interaction Scaling for Contact Networks
Sustainability
urban scaling
social interaction
contact networks
communication
individual connectivity
city size
author_facet Yusra Ghafoor
Yi-Shin Chen
Kuan-Ta Chen
author_sort Yusra Ghafoor
title Social Interaction Scaling for Contact Networks
title_short Social Interaction Scaling for Contact Networks
title_full Social Interaction Scaling for Contact Networks
title_fullStr Social Interaction Scaling for Contact Networks
title_full_unstemmed Social Interaction Scaling for Contact Networks
title_sort social interaction scaling for contact networks
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2019-05-01
description Urbanization drives the need for predictive and quantitative methods to understand city growth and adopt informed urban planning. Population increases trigger changes in city attributes that are explicable by scaling laws. These laws show superlinear scaling of communication with population size, asserting an increase in human interaction based on city size. However, it is not yet known if this is the case for social interaction among close contacts, that is, whether population growth influences connectivity in a close circle of social contacts that are dynamic and short-spanned. Following this, a network is configured, named <i>contact networks</i>, based on familiarity. We study the urban scaling property for three social connectivity parameters (degree, call frequency, and call volume) and analyze it at the collective level and the individual level for various cities around the world. The results show superlinear scaling of social interactions based on population for contact networks; however, the increase in level of connectivity is minimal relative to the general scenario. The statistical distributions analyze the impact of city size on close individual interactions. As a result, knowledge of the quantitative increase in social interaction with urbanization can help city planners in devising city plans, developing sustainable economic policies, and improving individuals&#8217; social and personal lives.
topic urban scaling
social interaction
contact networks
communication
individual connectivity
city size
url https://www.mdpi.com/2071-1050/11/9/2545
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