Chapter

Social Media for Government Services

pp 135-149

Date:

Detecting Bursty Topics of Correlated News and Twitter for Government Services

  • Takehito UtsuroAffiliated withUniversity of Tsukuba Email author 
  • , Yusuke InoueAffiliated withUniversity of Tsukuba
  • , Takakazu ImadaAffiliated withUniversity of Tsukuba
  • , Masaharu YoshiokaAffiliated withHokkaido University
  • , Noriko KandoAffiliated withNational Institute of Informatics

* Final gross prices may vary according to local VAT.

Get Access

Abstract

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.

Keywords

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