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Title: AppCAT: 基於手機應用程式評論情感分析和產品功能發掘 – 以 iOS 為例
AppCAT: Systematic Sentiment Analysis of Mobile Application Reviews
Authors: 黃書韋
Huang, Shu Wei
Contributors: 郁方
Yu, Fang
Huang, Shu Wei
Keywords: 手機應用程式
mobile application
sentiment analysis
Date: 2016
Issue Date: 2016-09-01 23:46:01 (UTC+8)
Abstract: 使用者對於手機應用程式的評論經常包含抱怨或是建議,此對於手機開發者用於改善使用者經驗和提升滿意度是很有幫助的。然而由於這些評論的品質和當中的雜訊使得手動去分析這些評論並且得到有價值的數據是困難的。
User reviews of mobile apps often contain complaints or suggestions which are valuable for app developers to improve user experience and satisfaction. However, due to the large volume and noisy-nature of those reviews, manually analyzing them for useful opinions is quite challenging. To address this problem, we propose Ap- pCAT, a sentiment and feature mining framework for automated review analysis. AppCAT defines the initial sets of keywords of those comments. And it use word similarity technique to expand the initial sets by grouping other keywords to find out the product features of those apps. Furthermore, AppCAT detects the sentiment and its subject(a product feature) of those reviews and figure out the user attitude towards those product feature of a specific app. AppCAT use those data to plot a bar chart to visualize those feature polarities for users to facilitate if they should consider this app. For the app developers, they can use this system to get the opinion overview of users as a basis of revision.
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Description: 碩士
Source URI:
Data Type: thesis
Appears in Collections:[資訊管理學系] 學位論文

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