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Common Growth Patterns for Regional Social Networks: A Point Process Approach.

Authors :
Tiandong Wang
Resnick, Sidney I.
Source :
Journal of Data Science. Jul2023, Vol. 21 Issue 3, p446-469. 24p.
Publication Year :
2023

Abstract

In this paper, we study macroscopic growth dynamics of social network link formation. Rather than focusing on one particular dataset, we find invariant behavior in regional social networks that are geographically concentrated. Empirical findings suggest that the startup phase of a regional network can be modeled by a self-exciting point process. After the startup phase ends, the growth of the links can be modeled by a non-homogeneous Poisson process with a constant rate across the day but varying rates from day to day, plus a nightly inactive period when local users are expected to be asleep. Conclusions are drawn based on analyzing four different datasets, three of which are regional and a non-regional one is included for contrast. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1680743X
Volume :
21
Issue :
3
Database :
Academic Search Index
Journal :
Journal of Data Science
Publication Type :
Academic Journal
Accession number :
171862737
Full Text :
https://doi.org/10.6339/21-JDS1021