Text Mining-Based Study on Consumer Satisfaction in the Mobile Phone Market

Author:

Zhou Qun1ORCID,Chen Meihua2,Chen Junying3,Chen Keren4,Tsai Sang-Bing5ORCID

Affiliation:

1. School of Information Resource Management, Renmin University of China, China

2. School of Emergency Management, Shandong Academy of Governance, China

3. School of Information Management, Wuhan University, China

4. Seoul School of Integrated Sciences and Technologies, South Korea

5. International Engineering and Technology Institute, Hong Kong

Abstract

In the current context of rapid technological advancement, smartphones have become an indispensable part of people's daily lives. This has led to an increasing focus on the satisfaction of consumers with smartphone products, as understanding consumer emotions and satisfaction has become a key factor for manufacturers and retailers to enhance the quality of products and services. This study delves into the satisfaction of consumers with smartphones in the market through an in-depth application of text mining techniques, leveraging advanced technologies such as natural language processing, sentiment analysis, and topic modeling. Our research methodology encompasses the process of collecting and preprocessing a substantial volume of consumer reviews from online shopping platforms. Subsequently, we apply Latent Dirichlet Allocation (LDA) for topic modeling and Extreme Learning Machine (ELM) for sentiment analysis.

Publisher

IGI Global

Reference33 articles.

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