Big Data for Social Media Evaluation: A Case of Wechat Platform Rankings in China




Qian Liu, Jingsi Ni, Jing Huang, Xiaochuan Shi

Lisa O’Conner

IEEE Second International Conference on Data Science in Cyberspace (DSC)

PublisherIEEE

2017

2017 IEEE Second International Conference on Data Science in Cyberspace Proceedings

528

533

6

978-1-5386-1599-7

DOIhttps://doi.org/10.1109/DSC.2017.28

http://ieeexplore.ieee.org/document/8005527/



Social media develop rapidly with a growing number of large-scale data generated. With big data, the demand for premiere content requires professional assessing and ranking system. Wechat, as the most popular social media platform, has become ubiquitous and important in China. Wechat public accounts ranking help business parts, government organs and users to approach high quality information effectively and maintain a sustainable environment for social media development. This paper introduced three different ranking systems in China on Wechat Public Accounts and analyze how they evaluate and assess big data generated though social media with their distinctive features: comprehensive, encouragement, regional. Further suggestions are proposed for the ranking systems with big data generated from social media platforms as well.



Last updated on 2024-26-11 at 22:14