Burstiness of human physical activities and their characterisation

Makoto Takeuchi () and Yukie Sano ()
Additional contact information
Makoto Takeuchi: University of Tsukuba
Yukie Sano: University of Tsukuba

Journal of Computational Social Science, 2024, vol. 7, issue 1, No 24, 625-641

Abstract: Abstract Human behaviour is heterogeneous and temporally fluctuates. Many studies have focused on inter-event time (IET) fluctuations and have reported that the IET distributions show a long-tailed distribution, which cannot be explained by a stationary Poisson point process. Such a phenomenon observed in IET distributions is known as burstiness. Burstiness has also been reported for human physical activity, but the mechanism underlying it has not been clarified. In this study, we prospectively collected human physical activity data while specifying the age of the subjects and their situations (for example, children’s play and adults’ housework), and we analysed their event time series data. We confirmed the burstiness in both children and adults. For the first time, burstiness was studied in physical activities of children between the ages of 2 and 5. This is important because it indicates that burstiness is not an acquired feature. We also confirmed that the IET distributions for each situation show a long tail. This result partially rejects the possibility that the burstiness of physical activities can be explained by multiple stationary Poisson process model. Our results are important for a deeper understanding of the human burst phenomenon and its mechanisms.

Keywords: Burst; Human dynamics; Children’s activities; Long-tailed distribution; Accelerometers; Wearables sensors (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s42001-024-00247-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jcsosc:v:7:y:2024:i:1:d:10.1007_s42001-024-00247-w

Ordering information: This journal article can be ordered from
http://www.springer. ... iences/journal/42001

DOI: 10.1007/s42001-024-00247-w

Access Statistics for this article

Journal of Computational Social Science is currently edited by Takashi Kamihigashi

More articles in Journal of Computational Social Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().