Common Growth Patterns for Regional Social Networks: a Point Process Approach
arXiv:1911.07902
Abstract
Although recent research on social networks emphasizes microscopic dynamics such as retweets and social connectivity of an individual user, we focus on 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 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.
arXiv comment28 pages, 17 figures
References in corpus (8)
- Organization of Growing Random Networks
- Degree Distributions of Growing Networks
- Exploring limits to prediction in complex social systems
- An estimation procedure for the Hawkes process
- Shaping Social Activity by Incentivizing Users
- Hawkes and INAR() processes
- A Tutorial on Hawkes Processes for Events in Social Media
- Correlated bursts and the role of memory range