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

被引:0
|
作者
Zhou, Qun [1 ]
Chen, Meihua [2 ]
Chen, Junying [3 ]
Chen, Keren [4 ]
Tsai, Sang-Bing [5 ]
机构
[1] Renmin Univ China, Sch Informat Resource Management, Beijing, Peoples R China
[2] Shandong Acad Governance, Sch Emergency Management, Jinan, Peoples R China
[3] Wuhan Univ, Sch Informat Management, Wuhan, Peoples R China
[4] Seoul Sch Integrated Sci & Technol, Seoul, South Korea
[5] Int Engn & Technol Inst, Hong Kong, Peoples R China
关键词
Consumer Satisfaction; ELM; LDA; Sentiment Analysis; Text Mining;
D O I
10.4018/JGIM.344835
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
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.
引用
收藏
页数:20
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