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Information Diffusion Model Based on Social Big Data

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Abstract

Users can access Weibo, a widely used social network platform, through mobile clients or PCs at any time for social interaction. This paper describes an information diffusion model based on the Weibo platform, which is used to measure information diffusion based on the extent of reposting on Weibo. First, the information diffusion of a Weibo post created in the evening is analyzed, and a quantitative analysis is conducted on the information diffusion within a particular period of time of night, targeting user behavior characteristics during that time, to further improve the accuracy of the model. Moreover, an information diffusion model based on superposition theory is proposed with respect to the participation of key users in the information diffusion process.

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Acknowledgments

This work was supported by the National Social Science Foundation of China under grant No. 13CTJ003 and by the China Postdoctoral Science Foundation under grant No. 2014M562025.

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Authors and Affiliations

  1. School of Information and Safety Engineering, Zhongnan University of Economics and Law, 182 Nanhu Ave, Hongshan, Wuhan, Hubei, 430073, China

    Dawei Jin, Xiao Ma, Yin Zhang & Han Yu

  2. State Key Laboratory for Novel Software Technology, Nanjing University, 22 Hankou Rd, Gulou Qu, Nanjing, Jiangsu, 210008, China

    Yin Zhang

  3. National University of Sciences and Technology, Islamabad, Pakistan

    Haider Abbas

  4. Florida Institute of Technology, 150 W University Blvd, Melbourne, FL, 32901, USA

    Haider Abbas

Authors
  1. Dawei Jin
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  2. Xiao Ma
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  3. Yin Zhang
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  4. Haider Abbas
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  5. Han Yu
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Corresponding author

Correspondence to Yin Zhang.

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Cite this article

Jin, D., Ma, X., Zhang, Y. et al. Information Diffusion Model Based on Social Big Data. Mobile Netw Appl 23, 717–722 (2018). https://doi.org/10.1007/s11036-018-1004-4

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  • DOI: https://doi.org/10.1007/s11036-018-1004-4

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