This study conducted text mining analysis of the review text data (13,615 accounts) posted on SNS by users of the public bike-sharing service in South Korea. A total of 11,954 reviews were processed with SKT KoBERT and classified them either positive or negative. Subsequently, various text mining techniques were used to determine the factors affecting the users’ polarity. The study results revealed that the identification of the positive and negative factors affecting service quality through an analysis of reviews by text mining contributes to the improvement of the public bike-sharing system.

中文翻译：

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文本挖掘以评估公共服务：公共自行车共享系统的案例

这项研究对韩国公共自行车共享服务用户在SNS上发布的评论文本数据（13,615个帐户）进行了文本挖掘分析。SKT KoBERT处理了总共11,954条评论，并将它们分为正面或负面。随后，使用各种文本挖掘技术来确定影响用户极性的因素。研究结果表明，通过文本挖掘对评论的分析来识别影响服务质量的正面和负面因素，有助于改善公共自行车共享系统。