當人們於日常生活中遇到問題或決策困境時，其往往透過網際網路環境之各社群網站尋求問題之解答及具參考價值之資料（本研究稱之為具專家特質之使用者的討論或回覆內容），並進而諮詢此類具專家特質之使用者，期望此類使用者以其豐富之專業知識提供問題解答或決策參考依據。另一方面，廠商、廣告商或代理商等業者亦常透過各社群網站尋找問題討論及回覆內容中具代表性或能引起廣泛共鳴之討論及回覆（本研究稱之為具領袖特質之使用者的討論或回覆內容），並期望委託具領袖特質之使用者以其能引起廣泛共鳴之表達方式或廣闊之人脈為其產品或服務進行廣告代言或發聲，以達到銷售量或知名度提升之成效。然而，當人們或廠商等業者欲自社群網站眾多問題討論及各使用者之回覆內容中篩選具參考價值之資料或具代表性、能引起廣泛共鳴之討論及回覆時，其往往需耗費大量時間閱讀問題討論及各使用者之回覆內容。
為解決上述問題，本研究乃先透過社群網站蒐集多份問題討論及各使用者之回覆，並解析其內容中具專家或領袖特質之使用者的討論與回覆內容所包含之特性；之後，本研究乃依據此些表達特性之解析結果發展一套「專家與領袖篩選」方法。而「專家與領袖篩選」方法可區分為「表達特性擷取」、「專家與領袖程度計算」、「專家與領袖判定」等三個階段。其中，「表達特性擷取」階段主要乃先自目標問題討論中擷取各使用者之回覆內容所具備的表達特性，並計算此些表達特性之篇幅；「專家與領袖程度計算」階段乃依據第一階段所得之目標問題討論與回覆內容結構化結果，推論各使用者符合專家與領袖之符合程度；「專家與領袖判定」階段乃依據第二階段所推論之符合程度判定目標問題討論與回覆內容中具專家特質或領袖特質之使用者。
未來，人們或廠商可依據本研究所發展的方法自社群網站之眾多討論及回覆內容中篩選具專家特質或領袖特質之使用者，並與具專家特質之使用者進行諮詢或與具領袖特質之使用者進行廣告代言等合作事宜。

As one has problems or decision issues, he/she always searches for the answers and the useful information on various social networks of Internet in order to acquire advices from the users with expertise. People depend highly on these users to provide some solutions or references for decision based on their own professional knowledge. On the other hand, manufacturers, advertiser or agencies always try to find the representative opinions of replies from the discussions in the online social networks, then they could identify the users who have leadership to endorse their products or service for increasing sales or visibility. However, people and vendors have to spend a lot of time sifting the useful informations from the user's replies. In order to solve the problems, this study develops a model for experts and leaders select of reply. It can be used to recommend experts and leaders. By applying the proposed model, people and advertisers can screen of experts or leaders and consult with experts or cooperation with the leaders very quickly.

摘要 I
ABSTRACT II
目錄 III
圖目錄 V
表目錄 VII
第一章、研究背景 1
1.1研究動機與目的 1
1.2研究步驟 5
1.3研究定位 8
第二章、文獻回顧 12
2.1社群網站使用者之回覆內容特質擷取 12
2.1.1以監督式方法擷取回覆內容特質 12
2.1.2以非監督式方法擷取回覆內容特質 15
2.1.3以混合式方法擷取回覆內容特質 21
2.2社群網站使用者之回覆內容價值評估 25
2.2.1以留言詞彙為基礎之回覆內容價值評估 25
2.2.2以留言特性為基礎之回覆內容價值評估 30
2.2.3結合留言詞彙與留言特性之回覆內容價值評估 34
2.3社群網站之專家與意見領袖推論 39
2.3.1針對一般性問題進行專家與意見領袖推論 39
2.3.2針對特定領域進行專家與意見領袖推論 42
第三章、以回覆內容為基礎之專家與領袖篩選模式 54
3.1現行之問題討論與使用者回覆解析 56
3.1.1回覆內容所具備之表達特性釐清 56
3.1.2專家與領袖於各子類篇幅多寡之判定 70
3.2表達特性擷取 74
3.3專家與領袖程度計算 85
3.4專家與領袖判定 98
3.5小結 110
第四章、系統規劃與架構 111
4.1系統核心架構 111
4.2系統功能架構 113
4.3資料模式定義 115
4.4系統功能運作流程 117
4.4.1系統功能操作流程 117
4.4.2系統資料傳遞流程 121
4.5系統開發工具 122
第五章、系統績效驗證與分析 124
5.1系統運作概況說明 124
5.2系統驗證方式說明 129
5.3系統驗證結果分析 134
第六章、結論與未來發展 172
6.1論文總結 173
6.2未來發展 175
參考文獻 177
附錄A、現行之問題討論與使用者回覆解析 183
附錄B、系統功能說明 333
附錄C、模式與系統於第二階段各週期之績效驗證結果 346

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