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Common Growth Patterns for Regional Social Networks: A Point Process Approach.
- 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]
- Subjects :
- *POINT processes
*SOCIAL networks
*POISSON processes
*SOCIAL dynamics
Subjects
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