The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Robust dynamic classes revealed by measuring the response function of a social system
Open accessAbstract
We study the relaxation response of a social system after endogenous and exogenous bursts of activity using the time series of daily views for nearly 5 million videos on YouTube. We find that most activity can be described accurately as a Poisson process. However, we also find hundreds of thousands of examples in which a burst of activity is followed by an ubiquitous power-law relaxation governing the timing of views. We find that these relaxation exponents cluster into three distinct classes and allow for the classification of collective human dynamics. This is consistent with an epidemic model on a social network containing two ingredients: a power-law distribution of waiting times between cause and action and an epidemic cascade of actions becoming the cause of future actions. This model is a conceptual extension of the fluctuation-dissipation theorem to social systems [Ruelle, D (2004) Phys Today 57:48–53] and [Roehner BM, et al. , (2004) Int J Mod Phys C 15:809–834], and provides a unique framework for the investigation of timing in complex systems.
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Imran, M., Castillo, C., Diaz, F., & Vieweg, S. (2015) · ACM Computing Surveys · doi:10.1145/2771588 · Cited by 804
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Zhao, Q., Erdogdu, M. A., He, H. Y., Rajaraman, A., & Leskovec, J. (2015) · Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/2783258.2783401 · Cited by 478
Metadata
- Authors
- Crane, R., & Sornette, D.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2008-10-14
- Volume
- 105
- Issue
- 41
- Pages
- 15649-15653
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2042034885
- Cited by
- 786
- References
- 20
- FWCI
- 52.33
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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