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Estimating the Number of Posts in Sina Weibo
School of Computer Science and Engineering, Southeast University, Nanjing, 211189, China.
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210023, China.
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
* Corresponding Author: Kai Dong. Email: .
Computers, Materials & Continua 2019, 58(1), 197-213. https://doi.org/10.32604/cmc.2019.03903
Abstract
Sina Weibo, an online social network site, has gained popularity but lost it in recent years. Now we are still curious on the number of posts in Sina Weibo in its golden age. Besides checking this number in Sina’s operating results, we aim to estimate and verify this number through measurement by using statistical techniques. Existing approaches on measurement always rely on the supported streaming application programming interface (API) which provides proportional sampling. However no such API is available for Sina Weibo. Instead, Sina provides a public timeline API which provides non-proportional sampling but always returns a (nearly) fixed number of s amples. In this paper, we present a novel method utilizing this API and estimate the number of posts in Sina Weibo in its golden age.Keywords
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