Temporal bipartite networks that describe how users interact with tasks or items over time have recently become available. Such temporal information allows us to explore user behavior in-depth. We propose two metrics, the relative switch frequency and distraction in time to measure a user’s sequential-tasking level, i.e. to what extent a user interacts with a task consecutively without interacting with other tasks in between. We analyze the sequential-tasking level of users in two real-world networks, an user-project and an user-artist network that record users’ contribution to software projects and users’ playing of musics from diverse artists respectively. We find that users in the user-project network tend to be more sequential-tasking than those in the user-artist network, suggesting a major difference in user behavior when subject to work related and hobby-related tasks. Moreover, we investigate the relation (rank correlation) between the two sequential-tasking measures and another 10 nodal features. Users that interact less frequently or more regularly in time (low deviation in the time interval between two interactions) or with fewer items tend to be more sequential-tasking in the user-project network. No strong correlation has been found in the user-artist network, which limits our ability to identify sequential-tasking users from other user features.

Original languageEnglish
Title of host publicationComplex Networks and Their Applications VII
Subtitle of host publicationProceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018
EditorsLuca Maria Aiello, Chantal Cherifi, Hocine Cherifi, Renaud Lambiotte, Pietro Lió, Luis M. Rocha
Place of PublicationCham
PublisherSpringer
Pages28-39
Number of pages12
Volume2
Edition1
ISBN (Electronic)978-3-030-05414-4
ISBN (Print)978-3-030-05413-7
DOIs
Publication statusPublished - 2019
EventCOMPLEX NETWORKS 2018: 7th International Conference on Complex Networks and their Applications - Cambridge, United Kingdom
Duration: 11 Dec 201813 Dec 2018
Conference number: 7

Publication series

NameStudies in Computational Intelligence
Volume813
ISSN (Print)1860-949X

Conference

ConferenceCOMPLEX NETWORKS 2018
CountryUnited Kingdom
CityCambridge
Period11/12/1813/12/18

ID: 48040622