UTILIZATION OF THE HIERARCHICAL DIRICHLET PROCESS TOPIC MODELING METHOD IN EVALUATING WEBSITE CONTENT QUALITY BASED ON USER REVIEWS
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Abstract
The evaluation of website content is important to ensure that the presented content aligns with users' needs and preferences. This can be accomplished by analyzing user reviews regarding the website's content. This research leverages the Hierarchical Dirichlet Process (HDP) method to automatically identify primary topics from 32 users' reviews, resulting in three main recurring topics: 'good', 'bug', and 'update'. Using the OSEMN framework, the final evaluation indicates that the 'good' topic exhibits the highest cosine similarity value compared to other topics. This signifies that the positive aspects highlighted in users' reviews regarding the website's content dominate and possess significant similarities among the reviews. These findings offer crucial insights into comprehending user evaluations of website content, serving as a basis for more effective and targeted content improvements moving forward.
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