Abstract
Various human activities were shown to exhibit heavy-tailed dynamics, dubbed "burstiness," which manifests itself as a fat tail in the waiting time distribution. Such a heavy-tailed activity crucially deviates from the traditional assumption of Poisson random activity which had been used for over a century in many theoretical and practical modelings of human activity-based problems. In this survey article, we will overview some recent studies on burstiness, focusing on (a) how to characterize the burstiness, (b) how to model the bursty human activity at the individual and population levels, and (c) how the bursty activity could modify the collective dynamics of spreading processes in social networks.
Original language | English |
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Title of host publication | Temporal Networks |
Publisher | Springer Verlag |
Pages | 41-64 |
Number of pages | 24 |
ISBN (Print) | 9783642364600 |
DOIs | |
Publication status | Published - 2013 |
Publication series
Name | Understanding Complex Systems |
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ISSN (Print) | 1860-0832 |
ISSN (Electronic) | 1860-0840 |
Bibliographical note
Funding Information:The authors would like to thank A.-L. Barabási, W.-k. Cho, I.-M. Kim, and A. Vazquez for the fruitful collaborations on the works reviewed in this article. This work was supported by Basic Science Research Program (No. 2011-0014191) through NRF grant funded by MEST.
ASJC Scopus subject areas
- Software
- Computational Mechanics
- Artificial Intelligence