使用文本挖掘分析手机应用商店中的用户反馈:以Google Fit为例

2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST) Pub Date : 2017-11-01 DOI:10.1109/ICAWST.2017.8256508

Y. Lai, Fen-Fen Huang, P. Chiou

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引用次数: 3

摘要

应用分发平台(或手机应用商店)为用户提供了一个提交对下载软件的反馈或评级的空间。这些平台对于软件提供商和用户在通信方面都变得非常重要。通过对大规模用户反馈数据的分析，可以得到用户需求的真实形象。这项研究分析了b谷歌Play中一个健康和健身追踪应用程序的4480个用户反馈。这项研究的结果表明，健康和健身相关应用的用户关心他们的身体活动记录和生理记录。记录包括跑道、距离、时间、慢跑或步行时消耗的卡路里等。此外，移动设备和可穿戴设备之间的连接对于用户来说非常重要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Analysis of user feedback in the mobile app store using text mining: A case study of Google Fit

Application distribution platforms (or mobile app stores) provide a space for users to submit feedback or ratings for downloaded software. These platforms have become very important for both software providers and users in communication. The really image of what users' demands can be obtained from the analysis of large-scale data of user feedback. This study analyzes 4,480 user feedbacks from a health and fitness-tracking app in the Google Play with text mining. The result of this study shows that the users of health and fitness-related apps are concerned about their physical activity records and physiological records. The records include track, distance, time, and calories burned during jogging or walking…etc. Besides, the connection between the mobile device and wearable devices is very important for users.

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来源期刊

2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)

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