Comprehensive Analysis of Consumer Sentiments and Topic Modeling on Samsung Z Fold Reviews Using NLP Techniques

This investigation utilizes sophisticated Natural Language Processing (NLP) methodologies to assess public sentiment and topic modeling regarding the Samsung Z Fold, analyzing a corpus of 15,454 YouTube comments. The research employs Latent Dirichlet Allocation (LDA) for topic identification and VADER for sentiment classification into positive, negative, and neutral categories. Results indicate that 48.5% of comments reflect positive sentiments, signifying a favorable consumer viewpoint on the Samsung Z Fold's innovative attributes and efficacy. In contrast, 18.3% of comments are negative, pointing to potential enhancements, especially in technical features and pricing strategies. The study additionally juxtaposes LDA with Hierarchical Dirichlet Process (HDP) and Latent Semantic Indexing (LSI).