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 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.