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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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’ 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’ 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 |
work_keys_str_mv |
AT yusraghafoor socialinteractionscalingforcontactnetworks AT yishinchen socialinteractionscalingforcontactnetworks AT kuantachen socialinteractionscalingforcontactnetworks |
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1725240860261482496 |