基于机器学习的移动健康App用户满意度研究
Research on User Satisfaction of Mobile Health App Based on Machine Learning
DOI: 10.12677/orf.2024.143329, PDF,   
作者: 吕雪佩：武汉科技大学管理学院，湖北 武汉
关键词: 用户评论；用户满意度；移动健康App；SnowNLP；User Reviews； User Satisfaction； Mobile Health App； SnowNLP
摘要: 移动健康在优化医疗资源配置、提高医疗效率等方面发挥着重要作用，而从活跃的在线评论中识别和分析用户关注的因素，有助于有针对性地提高用户满意度，增强产品竞争力。本文利用文本挖掘方法对移动健康App用户评论进行研究，基于词云图、word2vec和高频名词识别与用户满意度相关的维度，并利用频率统计和SnowNLP情感分析方法计算各维度的权重和情感得分。研究结果表明，影响移动健康App用户实际使用感受的维度主要包括服务、便利、质量、使用和费用5个方面；便利、服务和质量三个维度对移动健康App用户满意度影响较大，用户对使用维度最不满意。
Abstract: Mobile health plays an important role in optimizing the allocation of medical resources and improving medical efficiency. And identifying and analyzing the factors that users pay attention to from active online reviews can help to improve user satisfaction and enhance product competitiveness in a targeted way. In this study, we use text mining methods to study mobile health app user reviews, identify dimensions related to user satisfaction based on word cloud mapping, word2vec and high frequency nouns, and calculate the weights and sentiment scores of each dimension using frequency statistics and SnowNLP sentiment analysis methods. The results of the study show that the dimensions affecting the actual usage feelings of mobile health App users mainly include five aspects: service, convenience, quality, usage, and cost; the three dimensions of convenience, service, and quality have a greater impact on mobile health App user satisfaction, and users are most dissatisfied with the usage dimension.
文章引用：吕雪佩. 基于机器学习的移动健康App用户满意度研究[J]. 运筹与模糊学, 2024, 14(3): 935-945. https://doi.org/10.12677/orf.2024.143329

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