Social network sustainability for transport planning with complex interconnections

Abstract Social network analysis serves as sustainable mechanism to examine large-scale complex social connections, with heterogeneity and interdependencies posing as major challenges. In our research, a novel approach is developed to efficaciously discover critical nodes, designated as network bottlenecks. The bottleneck is considered crucial in propagating the flow of information in the network. This is further extended to extraction of relative checkpoint(s) that acts as probable sources of major inflows towards the respective bottleneck. These set of checkpoints can be considered for prior surveillance resulting the control of information outbursts towards bottleneck node. Viable domains for applicability of our proposed methodology include, road traffic monitoring, extremist content tracking, fake news inspection, uncloaking online terrorist movements, etc. For our experimentation, we have focussed on transport planning application to identify traffic hotspot regions and relative set of nodes acting as checkpoints. These checkpoints can serve as monitoring stations for controlling the traffic hence improving sustainable mobility over roads. Moreover, air purifying machines can also be deployed, hence facilitating improved air quality.

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