The Possibility of an Epidemic Meme Analogy for Web Community Population Analysis

  • Masao Kubo
  • Keitaro Naruse
  • Hiroshi Sato
  • Takashi Matubara
Conference paper

DOI: 10.1007/978-3-540-77226-2_107

Volume 4881 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Kubo M., Naruse K., Sato H., Matubara T. (2007) The Possibility of an Epidemic Meme Analogy for Web Community Population Analysis. In: Yin H., Tino P., Corchado E., Byrne W., Yao X. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2007. IDEAL 2007. Lecture Notes in Computer Science, vol 4881. Springer, Berlin, Heidelberg

Abstract

The aim of this paper is to discuss the possibility of understanding human social interaction in web communities by analogy with a disease propagation model from epidemiology. When an article is submitted by an individual to a social web service, it is potentially influenced by other participants. The submission sometimes starts a long and argumentative chain of articles, but often does not. This complex behavior makes management of server resources difficult and a more theoretical methodology is required. This paper tries to express these complex human dynamics by analogy with infection by a virus. In this first report, by fitting an epidemiological model to Bulletin Board System (BBS) logs in terms of a numerical triple, we show that the analogy is reasonable and beneficial because the analogy can estimate the community size despite the submitter’s information alone being observable.

Keywords

Kermack–McKendrick models SIR BBS SNS Web Mining 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Masao Kubo
    • 1
  • Keitaro Naruse
    • 2
  • Hiroshi Sato
    • 1
  • Takashi Matubara
    • 1
  1. 1.National Defense Academy of Japan, Dep. of Computer Science, Hashirimizu 1, Yokosuka, Kanagawa,239-8686Japan
  2. 2.Univ. of Aizu, Dep. of Computer Software, Aizu-Wakamatsu, Fukushima-ken, 965-8580Japan