Detecting Bursty Topics of Correlated News and Twitter for Government Services

  • Takehito UtsuroEmail author
  • Yusuke Inoue
  • Takakazu Imada
  • Masaharu Yoshioka
  • Noriko Kando


This chapter presents a framework of detecting bursty topics of correlated news and twitter, and discusses how to integrate the framework into government services. Especially, as a specific application of the proposed framework of detecting bursty topics of correlated news and twitter, this chapter gives an example of collecting news and twitter that are related to “the 2012 London Olympic game” and applying the proposed framework.


Time series news and twitter Topic model Kleinberg’s burst model 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Takehito Utsuro
    • 1
    Email author
  • Yusuke Inoue
    • 1
  • Takakazu Imada
    • 1
  • Masaharu Yoshioka
    • 2
  • Noriko Kando
    • 3
  1. 1.University of TsukubaTsukubaJapan
  2. 2.Hokkaido UniversitySapporoJapan
  3. 3.National Institute of InformaticsTokyoJapan

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