Abstract
Research on human online activities usually assumes that total activity T increases linearly with active population P, that is, T Pγ(γ=1). However, we find examples of systems where total activity grows faster than active population. Our study shows that the power law relationship T Pγ(γ>1) is in fact ubiquitous in online activities such as microblogging, news voting, and photo tagging. We call the pattern "accelerating growth" and find it relates to a type of distribution that changes with system size. We show both analytically and empirically how the growth rate γ associates with a scaling parameter b in the size-dependent distribution. As most previous studies explain accelerating growth by power law distribution, the model of size-dependent distribution is worth further exploration. © 2011 American Physical Society.
| Original language | English |
|---|---|
| Article number | 026113 |
| Journal | Physical Review E - Statistical, Nonlinear, and Soft Matter Physics |
| Volume | 84 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 15 Aug 2011 |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
One of us (J.Z.) acknowledges the support from the National Natural Science Foundation of China under Grant No. 61004107.
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