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The main goal is to uncover insights into the prevalent topics within each star review. I specifically undertook the challenge of conducting topic modeling for the 1-Star Reviews. Moreover, the project seeks to evaluate and pinpoint the most effective algorithm for this task. The three algorithms employed in this project are **Latent Dirichlet Allocation (LDA)**, **Non-Negative Matrix Factorization (NMF)**, and **BERTopic**. The evaluation metrics utilized encompass **Topic Diversity** and **Coherence Score**.\n\n# Flow of Analysis\n\n\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"https://github.com/Rlvtick/Topic-Modeling-Shopee-Reviews/assets/104807940/21e2d6c3-b856-41a1-a004-7f2fab4435e5\" alt=\"Flow\"\u003e\n\u003c/div\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frlvtick%2Ftopic-modeling-shopee-reviews","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frlvtick%2Ftopic-modeling-shopee-reviews","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frlvtick%2Ftopic-modeling-shopee-reviews/lists"}