Cluster-N-Engage: A New Framework for Measuring User Engagement of Website With User Navigational Behavior

Citation

Lim, Zhou Yi and Ong, Lee Yeng and Leow, Meng Chew (2023) Cluster-N-Engage: A New Framework for Measuring User Engagement of Website With User Navigational Behavior. IEEE Access, 11. pp. 112276-112292. ISSN 2169-3536

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Abstract

User engagement is a part of user experience that measures how attracted the users are in using a certain product or services. The level of user attention while navigating a website is a key factor in determining its effectiveness. Web usage mining can be performed on the weblog of a website to extract user navigational behavior and gain valuable insights into the useful activities of the users. The user navigational behavior can then be further evaluated to measure the user engagement of the website. This paper presents a new framework that uses user navigational behavior extracted from web usage mining to measure the engagement level of the users on the website. In this proposed framework, web session clustering is first performed on the pre-processed weblog to group similar user access patterns from web sessions. After that, four proposed engagement metrics, which are the hourly activeness, the hourly traffic, the daily activeness, and the daily traffic are calculated for each cluster to determine the engagement level of the users on the website. According to the engagement level determined by the user engagement metrics, an attention score is formulated to show how attracted the users in the session cluster are to the website. In this paper, two weblogs from different websites are used to measure their user engagement with the Cluster-N-Engage framework. The framework shows that attention score can assess the website’s effectiveness in achieving its objectives.

Item Type: Article
Uncontrolled Keywords: Web usage mining.
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 01 Dec 2023 01:30
Last Modified: 01 Dec 2023 01:30
URII: http://shdl.mmu.edu.my/id/eprint/11890

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