Document Type : Articles
1 University of Missouri, Columbia, United States
2 University of South Florida, United States
3 Southeast University, China
As Google Analytics becomes increasingly popular, more detailed records of users’ behaviors can be captured and analyzed to better understand the performance of websites. However, current Google Analytics related research usually draws conclusions from rough estimation based on the observation of the dashboard or other basic statistical processing of the data. This study aims to provide a more accurate and informative analysis from both temporal and geospatial perspectives via clustering and GIS application. The results obtained from a resource website case study demonstrate that the proposed method is able to help web managers better examine the temporal effect on users’ visiting patterns based on accurate mathematical computation as well as provides more geographical insight into website performance through the constructed density measure and 3D graphic presentation. By offering in-depth quantitative information relying on mining data from web logs, such a study can help web stakeholders make better decisions on how to maintain and improve the websites, especially adjusting resources by considering temporal fluctuations and inequity in geographical distribution.
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