Web behavior analysis in social life logging

Collection of web behavior relies on self-report and web logs in daily life. The self-report is derived on memory and can seem ambiguous for analyzing web behavior. It is necessary to quantitatively measure these web behaviors to see the changes over time. Individuals tied by the same emotion become...

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Bibliographic Details
Published inThe Journal of supercomputing Vol. 77; no. 2; pp. 1301 - 1320
Main Authors Jo, Youngho, Lee, Hyunwoo, Cho, Ayoung, Whang, Mincheol
Format Journal Article
LanguageEnglish
Published New York Springer US 01.02.2021
Springer Nature B.V
Subjects
Compilers
Computer Science
Interpreters
Processor Architectures
Programming Languages
Social networks
Synchronism
Life logging
Category
Emotion
Web behavior
Content
Social networking
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Summary:Collection of web behavior relies on self-report and web logs in daily life. The self-report is derived on memory and can seem ambiguous for analyzing web behavior. It is necessary to quantitatively measure these web behaviors to see the changes over time. Individuals tied by the same emotion become a group, and its members synchronize with each other. Therefore, this study is to propose a web behavior model and its collecting and analyzing methods. Additionally, this study is to create a group using the synchronization of behavior patterns and social networking to provide insight into enhanced marketing.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-020-03304-z