Self-exciting point process modeling of conversation event sequences

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

40 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationTemporal Networks
PublisherSpringer Verlag
Number of pages20
ISBN (Print)9783642364600
Publication statusPublished - 2013
Externally publishedYes

Publication series

NameUnderstanding Complex Systems
ISSN (Print)1860-0832
ISSN (Electronic)1860-0840

ASJC Scopus subject areas

  • Software
  • Computational Mechanics
  • Artificial Intelligence


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