Event Detection in Twitter: Methodological Evaluation and Structural Analysis of the Bibliometric Data

  • Musa Ibarhim M. Ishag
  • Kwang Sun Ryu
  • Jong Yun Lee
  • Keun Ho RyuEmail author
Part of the Studies in Computational Intelligence book series (SCI, volume 769)


Twitter—a social networking service is increasingly becoming an important source of news and information for various aspects of our life. However, harnessing reliable sources is both tedious and challenging. Algorithms for mining and detecting events from Twitter have been developed. In this paper, event detection techniques are investigated. In essence, a theoretical comparison of the state-of-the-art event detection algorithms is performed along with highlights to the current issues and proper suggestions to mitigate them. In addition, a knowledge domain map analysis using CiteSpace is applied to the bibliometric data in the field in order to explore the structural dynamics of the research in this domain.


Twitter Event detection Bibliometric analysis CiteSpace 



This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (No. 2017R1A2B4010826), and MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2017-2013-0-00881) supervised by the IITP (Institute for Information & Communications Technology Promotion).


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Musa Ibarhim M. Ishag
    • 1
  • Kwang Sun Ryu
    • 1
  • Jong Yun Lee
    • 2
  • Keun Ho Ryu
    • 1
    Email author
  1. 1.College of Electrical and Computer EngineeringChungbuk National UniversityCheongjuSouth Korea
  2. 2.Department of Software EngineeringChungbuk National UniversityCheongjuSouth Korea

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