Self-exciting point process modeling of conversation event sequences

Naoki Masuda*, Taro Takaguchi, Nobuo Sato, Kazuo Yano

*この研究の対応する著者

研究成果: Chapter

30 被引用数 (Scopus)

抄録

Self-exciting processes of Hawkes type have been used to model various phenomena including earthquakes, neural activities, and views of online videos. Studies of temporal networks have revealed that sequences of social interevent times for individuals are highly bursty. We examine some basic properties of event sequences generated by the Hawkes self-exciting process to show that it generates bursty interevent times for a wide parameter range. Then, we fit the model to the data of conversation sequences recorded in company offices in Japan. In this way, we can estimate relative magnitudes of the self excitement, its temporal decay, and the base event rate independent of the self excitation. These variables highly depend on individuals. We also point out that the Hawkes model has an important limitation that the correlation in the interevent times and the burstiness cannot be independently modulated.

本文言語English
ホスト出版物のタイトルTemporal Networks
出版社Springer Verlag
ページ245-264
ページ数20
ISBN(印刷版)9783642364600
DOI
出版ステータスPublished - 2013
外部発表はい

出版物シリーズ

名前Understanding Complex Systems
ISSN(印刷版)1860-0832
ISSN(電子版)1860-0840

ASJC Scopus subject areas

  • ソフトウェア
  • 計算力学
  • 人工知能

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