Nearcasting forwarding behaviors and information propagation in Chinese Sina-Microblog

Fulian Yin; Xueying Shao; Jianhong Wu; Fulian Yin; Xueying Shao; Jianhong Wu

doi:10.3934/mbe.2019268

Mathematical Biosciences and Engineering

2019, Volume 16, Issue 5: 5380-5394. doi: 10.3934/mbe.2019268

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Research article

Nearcasting forwarding behaviors and information propagation in Chinese Sina-Microblog

1.
College of Information and Communication Engineering, Communication University of China, Beijing, 100024, P.R. China
2.
Laboratory for Industrial and Applied Mathematics, York University, Toronto, M3J1P3, Canada

Received: 19 February 2019 Accepted: 19 April 2019 Published: 11 June 2019

As the largest social media in China, the Sina-Microblog plays an important role in public opinion dissemination. Despite intensive efforts in understanding the information propagation dynamics, the use of a simple outbreak model to generate summative indices that can be used to characterize the time series of a single Weibo event has not been attempted. This work fills this gap, and illustrates the potential of using a simple outbreak model in conjunction with the historical data about the cumulative forwarding users for nearcasting the propagation trend.
- nearcasting,
- information propagation,
- forwarding behaviors,
- SFI model,
- Chinese Sina-Microblog
Citation: Fulian Yin, Xueying Shao, Jianhong Wu. Nearcasting forwarding behaviors and information propagation in Chinese Sina-Microblog[J]. Mathematical Biosciences and Engineering, 2019, 16(5): 5380-5394. doi: 10.3934/mbe.2019268

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Abstract

As the largest social media in China, the Sina-Microblog plays an important role in public opinion dissemination. Despite intensive efforts in understanding the information propagation dynamics, the use of a simple outbreak model to generate summative indices that can be used to characterize the time series of a single Weibo event has not been attempted. This work fills this gap, and illustrates the potential of using a simple outbreak model in conjunction with the historical data about the cumulative forwarding users for nearcasting the propagation trend.

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