A4 Refereed article in a conference publication
Big Data for Social Media Evaluation: A Case of Wechat Platform Rankings in China
Authors: Qian Liu, Jingsi Ni, Jing Huang, Xiaochuan Shi
Editors: Lisa O’Conner
Conference name: IEEE Second International Conference on Data Science in Cyberspace (DSC)
Publisher: IEEE
Publication year: 2017
Book title : 2017 IEEE Second International Conference on Data Science in Cyberspace Proceedings
First page : 528
Last page: 533
Number of pages: 6
ISBN: 978-1-5386-1599-7
DOI: https://doi.org/10.1109/DSC.2017.28(external)
Web address : http://ieeexplore.ieee.org/document/8005527/(external)
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.