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Analysis of collective action propagation with multiple recurrences

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Abstract

Collective action propagation, which can be as large as billions of people adopting Facebook or as small as a few researchers citing a paper, exists in various real-life scenarios. Here, we perform a large-scale investigation of collective action propagation with “recurrence” phenomena. We consider actions that propagate in a social network with multiple communities and find the growth in the propagation breadth of collective action can be explained by a simple mathematical model with an analytical solution. We use datasets on the growth of total views of TED and YouTube videos, the prize pool of Dota 2 tournaments, and a total gross of movies to investigate collective action propagation with recurrence phenomena. Experimental results reveal that our model can capture universal features of collective action propagation, validating the idea that collective action propagation with recurrence results from an action being transmitted from communities to communities.

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Acknowledgements

This work was supported by National Science Foundation of China (61703355) and Guangzhou Science and Technology Plan Project of China under Grant 201904010224 and 201804010292. Also Thanks are due to Dr. Jing Jing Su for her advice and help.

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Authors and Affiliations

  1. School of Computer, South China Normal University, Guangzhou, China

    Choujun Zhan, Zhenhua Huang & Qizhi Zhang

  2. School of Electrical and Computer Engineering, Nanfang College of Sun Yat-Sen University, Guangzhou, China

    Fujian Wu & Wei Jiang

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  1. Choujun Zhan
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  2. Fujian Wu
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  3. Zhenhua Huang
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  4. Wei Jiang
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  5. Qizhi Zhang
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Correspondence to Qizhi Zhang.

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Zhan, C., Wu, F., Huang, Z. et al. Analysis of collective action propagation with multiple recurrences. Neural Comput & Applic 32, 13491–13504 (2020). https://doi.org/10.1007/s00521-020-04756-3

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  • DOI: https://doi.org/10.1007/s00521-020-04756-3

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