Journal of Combinatorial Optimization

, Volume 28, Issue 3, pp 613–625 | Cite as

A short-term trend prediction model of topic over Sina Weibo dataset

  • Juanjuan Zhao
  • Weili Wu
  • Xiaolong Zhang
  • Yan Qiang
  • Tao LiuEmail author
  • Lidong Wu


Microblog has become a popular social network service. It provides a new communication platform for information acquisition, sharing and spreading. In addition to presenting daily-life reports from users, microblog also reports unexpected events, which get broad attention. How to forecast such unexpected events as early as possible? In this paper, we propose a short-term trend prediction model of topics in Sina Weibo, the most popular microblog service in China. Based on real microblog data, we first analyze which Weibo data attributes have influence on the spreading of topics, and then build a topic spreading model. Further, we develop a model of short-term trend prediction of topics. With dataset from Weibo, we test our algorithm and analyze the experimental data which shows that the proposed model can give a short-term trend prediction of Weibo topic.


Social networks Sina Weibo Analysis of Weibo properties  Prediction model Microblog 



This study was supported by the National Natural Science Foundation of China (Grant No. 61202163, 61240035, 61373100); Natural Science Foundation of Shanxi Province (Grant No. 2012011015-1) and Programs for Science and Technology Development of Shanxi Province (Grant No. 20120313032-3). This work was also supported in part by the US National Science Foundation (NSF) under Grant No. CNS-1016320 and CCF-0829993.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Juanjuan Zhao
    • 1
  • Weili Wu
    • 2
  • Xiaolong Zhang
    • 3
  • Yan Qiang
    • 1
  • Tao Liu
    • 1
    Email author
  • Lidong Wu
    • 2
  1. 1.College of Computer Science and TechnologyTaiyuan University of TechnologyTaiyuanChina
  2. 2.Department of Computer ScienceUniversity of Texas at DallasRichardsonUSA
  3. 3.College of Information Sciences and TechnologyPennsylvania State UniversityState CollegeUSA

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