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

Year: 2025

Type: article

Abstract: 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).

Source: Journal of Information Systems Engineering & Management

DOI: 10.52783/jisem.v10i29s.4460

Author: Zidane Zulfikar Supratman, Mochamad Yudha Febrianta

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4409144963

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