Abstract
This paper takes Weibo users as the research object, and extracts two dimensions from the point of view of user relationship: Micro-bo concern number, micro-blog fans number, and on this basis to generate fans rate indicator. Through the Python Network crawler to acquire and analysis data, this paper has obtained the exponential function model and cumulative distribution model of the fans rate distribution, and verified the correlation between fans rate and Weibo influence. It has higher practical application value.
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Acknowledgment
Thanks for support from Science and technology department of Shaanxi province granted by 2016GY-106, social science foundation of Shaanxi province with number 15JZ047 and key laboratory research plan of Shaanxi province department numbered by 2015R026.
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Yangpeng, Z., Peng, L. (2018). Sina Weibo User Influence Research. In: Tavana, M., Patnaik, S. (eds) Recent Developments in Data Science and Business Analytics. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-72745-5_55
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DOI: https://doi.org/10.1007/978-3-319-72745-5_55
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