Spatiotemporal Network Diffusion Codes and Data

Information, ideas, and diseases, or more generally, contagions, spread over space and time through individual transmissions via social networks, as well as through external sources. A detailed picture of any diffusion process can be achieved only when both a good network structure and individual diffusion pathways are obtained. The advent of rich social, media and locational data allows us to study and model this diffusion process in more detail than previously possible. Nevertheless, how information, ideas or diseases are propagated through the network as an overall process is difficult to trace. This propagation is continuous over space and time, where individual transmissions occur at different rates via complex, latent connections.\par

To tackle this challenge, a probabilistic spatiotemporal algorithm for network diffusion (STAND) is developed based on the survival model in this research. Both time and spatial distance are used as explanatory variables to simulate the diffusion process over two different network structures. The aim is to provide a more detailed measure of how different contagions are transmitted through various networks where nodes are geographic places at a large scale.

Works

article
V1 published
Creators
  1. Fangcao Xu
Deposited July 20, 2019
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Open Access
article
V1 published
Creators
  1. Fangcao Xu
Deposited July 20, 2019
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Open Access
article
V1 published
Creators
  1. Fangcao Xu
Deposited July 20, 2019
Access
Open Access
article
V1 published
Creators
  1. Fangcao Xu
Deposited July 20, 2019
Access
Open Access
article
Creators
  1. Fangcao Xu
Deposited July 20, 2019
Access
Open Access
article
V1 published
Creators
  1. Fangcao Xu
Deposited July 20, 2019
Access
Open Access

Metadata

Title Spatiotemporal Network Diffusion Codes and Data
Creator
  1. Fangcao Xu
Keyword
  1. STAND Algorithm; Spatiotemporal Network Diffusion; Survival Analysis; Probabilistic Function
Subject
  1. Social networks
  2. Geography
DOI doi:10.26207/g7n9-tm98
Deposited at July 03, 2019

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