Social Interaction Scaling for Contact Networks

Abstract

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 contact networks, 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.