Apple App Store模式的成功不只改寫了全球行動通訊應用軟體的商業模式，更推動了資通訊前瞻性與新興產業策略性的發展。然而在過去的研究中，卻少有學者關注行動應用軟體商店驚人的銷售績效背後，到底受到哪些類型的網路口碑或變數的影響，而對於造成改變的原因亦少有學者去作深入之探究。
　　本研究是網路口碑對於行動應用軟體銷售指標的實證研究、運用文字探勘與意見分析技術配合詞組探索規則(Heuristic Rule)量化網路口碑。本研究採用市場品牌領導者Apple App Store台灣地區的官方評論系統和付費銷售排行榜作為研究對象，以台灣地區2011年整年度銷售最好的十款行動應用軟體每個星期日當天的排名變化，再結合網路口碑、資訊系統成功模式、文字探勘與意見分析，提出一個整合性的架構，探討台灣地區的智慧型手機用戶在購買行動應用軟體時，是否會受不同型態的網路口碑(跟據最新十篇的線上文字評論及十篇評論之平均評等)、產品價格而產生變動。研究發現與結論如下列所示；
1. 整體而言，本研究所提出的文字探勘方法能夠有效的預測消費者口碑對銷售排名的影響。而「系統性文字評論之語意分數」顯著的影響2010-2011年間Apple App Store付費排行上銷售最好的前十大行動應用軟體的銷售表現。
2. 將十款行動應用軟體做更進一步分群後發現：對於「功利型行動應用軟體」來說，「系統性文字評論之語意分數」和「產品價格」均能顯著的影響其排行榜上的銷售指標。
3. 對於「享樂型行動應用軟體」來說，「系統性文字評論之語意分數」、「服務性文字評論之語意分數」、「平均評等」和「產品價格」均顯著的影響其排行榜上的銷售指標，驗證了網路口碑中三種不同類型的線上文字評論在實務上對於不同產品的銷售指標(Apple App Store付費排行上的名次)有不同程度的顯著影響力。

關鍵字: 行動應用軟體、網路口碑、文字探勘、意見分析、詞組探索規則、語意分數

The App Store's success has not only changed the business model of mobile software, but also expedited the development of ICT and newly developed industries. Eletronic word of mouth (e-WOM) has become an influential power in consumer decision making. However, not much previous research has examined the effect of eWOM on sales performance of mobile App.
This research is an empirical research that is focused on the issue of how eWOM affect the sales performance of mobile App. I used text mining and heuristic rules to classify and analyze the mood of the eWOMs and empirical examined their effects. The eWOM and sales ranking of the top ten Apple’s App’s in Taiwan in 2011 were retrieved for this research. Each eWOM was classified into system and service-related comments (based on the information system success model). These comments were then classified into their emotional scale. The top ten App’s were classified into utilization and hedonic Apps’. The data were then combined with price and the average ranking to examine their effects on the sales ranking. Major findings include the following:

1. Overall, our proposed method for analyzing eWOM can effectively predict the sales ranking of an App. The eWOM score of system quality had significant effect on the sales ranking of the top ten App in the Apple’s App Store in 2011.

2. When the top ten App’s were divided into utilization and hedonic groups, we found that the score of system quality and price had significant effect on the sales ranking.

3. For hedonic App’s, all four factors (system quality score, service quality score, average rating, and price) had significant effect on the sales ranking.

Keywords: App Store, mobile software, eWOMs, text mining, heuristic rules

第一章、 緒論 1
第一節、 研究背景 1
第二節、 研究動機 2
第三節、 研究問題與目的 5
第四節、 研究流程與步驟 6
第五節、 論文架構 8
第二章、 文獻探討 9
第一節、 行動應用軟體發展與銷售平台的排名 9
壹、 行動應用軟體之發展 9
貳、 行動應用軟體的銷售平台與Apple App Store排行榜 10
第二節、 各種型態的口碑對銷售績效的影響 14
壹、 傳統口碑(WOM)的發展與對銷售績效的影響 14
貳、 網路口碑(eWOM)的發展與對銷售面的影響 15
第三節、 網路口碑的類型 19
壹、 線上文字評論(Online Reviews) 19
貳、 平均評等(Average Rating) 21
第四節、 文字探勘與意見分析 22
壹、 文字探勘 22
貳、 意見分析(opinion analysis)與正負向種子辭彙建立 23
參、 情感語意分數之計算 26
第五節、 線上文字評論的訴求主題 26
壹、 網路口碑中訴求主題的傳統分類 27
貳、 資訊系統成功模式 28
第六節、 產品價格變動對銷售指標的影響 29
第七節、 行動應用軟體的產品分類 30
第三章、 研究架構與方法 32
第一節、 研究架構 32
第二節、 研究模型 38
第三節、 研究對象 39
第四節、 研究假說 39
第五節、 研究方法 39
第四章、 意見分析的方法 41
壹、 資料蒐集與數據編碼 41
貳、 網路文字評論蒐集與相關程式撰寫 42
參、 資料前置處理、中文斷詞與詞性標註 46
肆、 情感特徵詞篩選與建立詞性組探索規則 48
伍、 建立正負向種子詞彙與線上文字評論的訴求主題 52
陸、 透過正負向詞彙計算語義分數 65
第五章、 研究模式驗證 67
第一節、 樣本特性分析 67
第二節、 研究假說之檢定 68
第六章、 結論與建議 73
第一節、 研究發現與結論 73
壹、 學術面 75
貳、 實務面 76
參、 研究限制與展望 76
參考文獻 78

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