User Behavior Analysis of Location-Based Social Network

Jun Zeng, Xin He, Yingbo Wu, Sachio Hirokawa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    User behavior changes over time under the influence of their activities. We contend that these activities are non-random behavior and have a desire to explore the underlying information behind these changes. In this paper, we analyze user behavior by using the check-in data in Location Based Social Networks (LBSNs), and examine whether they have the features of trend, periodicity and surprise or not. We explore some dynamics behaviors of people through their check-in times, and divide time into annually, monthly and even weekly analysis to find out the pattern of their behavior. Eventually, we found the check-in data do exhibit these three features by analyzing them deeply. The analytical work lays the foundation for the further recommendation research.

    Original languageEnglish
    Title of host publicationProceedings - 2018 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages21-25
    Number of pages5
    ISBN (Electronic)9781538674475
    DOIs
    Publication statusPublished - Jul 2 2018
    Event7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018 - Yonago, Japan
    Duration: Jul 8 2018Jul 13 2018

    Publication series

    NameProceedings - 2018 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018

    Conference

    Conference7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018
    CountryJapan
    CityYonago
    Period7/8/187/13/18

    All Science Journal Classification (ASJC) codes

    • Computer Networks and Communications
    • Communication
    • Information Systems
    • Information Systems and Management
    • Education

    Fingerprint Dive into the research topics of 'User Behavior Analysis of Location-Based Social Network'. Together they form a unique fingerprint.

    Cite this