社會網路分析（social network analysis）將社會關係以網路形式表示，從原本純粹分析社會互動的工具，到近年來被廣泛被應用在社會學、組織研究、資訊科學、生物學、語言學等各種領域，藉由引入數學圖學理論與與日益精進的電腦處理能力，使得社會網路分析能從有別於以往的角度找出個體間行動的規律；而詞義相似度（word similarity）是資訊檢索等技術發展的基礎課題之一，近年來對詞義相似度的量測有許多方法的提出。 本研究針對英語字詞利用社會網路分析這樣的工具，藉由提出不同的網路建構方式，以語料庫為資料來源，設定網路節點與連結關係，以共現網路（co-occurrence networks）為基礎，經由改變產生與篩選的條件，觀察以社會網路分析已有的性質或指標做調整，是否可以對詞義相似度提供另一種量測方式；同時以目前詞義相似度研究上已有同義詞標準評比對前述產生的網路與所計算的性質做驗證，並進一步探討使用社會網路分析在詞義相似度研究上的適用性。

當面對總體蘊藏資訊量極為龐大，單筆資訊則較為零碎的資料來源時，社會網路分析同時兼具微觀及巨觀分析特點的方式，提供了一獨特的切入分析角度。目前在社會網路分析領域中，針對網路性質所發展的分析指標等相關理論，大多以1-mode網路為主要的探討模式，對於2-mode網路模式下的著墨則較為稀少。在本研究論文中，以政府人事異動資料庫為主要資料來源，建構出同時具有人物以及職務兩種不同類型節點的2-mode網路，並選擇以適用於2-mode網路模式下的連結預測理論為主要核心，建置出職務接替人選預測系統，其後透過配合不同的實驗模式設計進行接替人選的預測行動，希望能以此來探討單一職位對於其未來接替人選的考量上，受到其歷任人員職務歷程的影響程度。 實驗數據結果顯示，本研究所建置出的接替人選預測系統，對於不同的職務分類層級以及針對不同部門間的職務預測，均會產生不同的預測成效，而這些成果均可適切反映出因應於升遷法制規範或是部份部門於專業知識上的需求條件，因而使得其在對於職位接替人選的考量上，較易受到歷任人選於職務歷程方面的影響。 / When coping with the information source which can store quite high information load in total while one piece of that tends to be fragmentary, Social Network Analysis provides a unique viewpoint to contain analyzing characteristics from both of microcosmic and macrocosmic perspectives. To date, when it comes to theories related to analysis indicator established from different analyzing characteristics in the field of Social Network Analysis, effort is mainly made to explore 1-mode network. By contrast, little emphasis is put on 2-mode network. In this study, the database of government’s personnel change is adopted as the major information source. This study then establishes a 2-mode network with two different types of node, that is, personnel and position. Choosing Link Prediction Theory as the major core with its applicability of 2-mode network, the present study sets up a prediction system of position taking-over candidate. Then, in accordance with different designs of experimental model, the prediction is conducted in an attempt to investigate whether the consideration of future taking-over candidate for a certain position would be influenced by position courses of all past personnel in this position. According to the experimental data, the prediction system of position taking-over candidate established in this study shows different prediction efficiency when predicting different position layers and positions from different sectors. These results all appropriately reflect that the consideration of position taking-over candidate is more easily influenced by position courses of past personnel due to the rules of promotion and the conditions of professional knowledge in some sectors.

在傳統資訊系統開發過程中，需求分析通常被視為非常關鍵的步驟。但在Web-based的資訊系統開發中，需求分析卻很少被提及。這篇論文提要主要強調傳統資訊系統與Web資訊系統的差異，並提出一個社群導向系統的需求擷取架構。這個架構將需求擷取分成三個階段：初步分析、關鍵使用者需求分析以及一般使用者的反應。目前Web的開發技術以及社群設計的方法，通常只做初步分析，在系統開發過程中並不直接蒐集使用者的需求。本文提出的三階段架構強調關鍵使用者的重要性，並建議採用社會網路分析作為辦識關鍵使用者的工具。 關鍵使用者區分為資訊、溝通、交易以及娛樂四大類別。初步預試這四種不同類別的關鍵使用者是否會產生較多該類別的資訊需求，以及是否產生較多的需求總數。結果發現只有資訊的關鍵使用者產生較多的資訊需求以及總需求，而其他類別的關鍵使用者與產生需求數量上的關係都不顯著。而另一項有趣的發現是：20％資訊關鍵使用者可以產生大約80％的需求總數，與Pareto規則的預測相似。資訊關鍵使用者的意見是否可以代表全體的意見，預試的結果顯示80％以上的需求重要性評估，關鍵使用者與全體的意見沒有顯著差異。 實地研究採用則探究兩個線上社群，一為關係導向社群，另一則為興趣社群，用以探索使用者角色，涉入程度以及需求知覺間的關係。多變量共變數分析的結果顯示：去除涉入程度的影響後，使用者角色會顯著影響使用者對於需求的知覺，雖然影響的方式以及程度並不相同。高涉入的使用者對於需求的敏銳度，普遍比低涉入者需求要高，並不因為需求種類而有所不同，最後並討論管理的意涵以及日後的研究方向。 / Although the requirement analysis is generally considered a critical stage in traditional information systems development (ISD), but it does not get enough attention in most Web-based information systems development (WISD) or the emerging community-oriented design. The thesis highlighted the difference between ISD and WISD, and proposed a three-stage model of user requirements elicitation for community-oriented design. This model divides the requirements definition in three stages: initial analysis, key user requirements elicitation, and regular user responses. Most current WIS and community design methodologies consider only initial analysis or attempt to build common system architecture, and neglect actual users’ requirements. Key user input is emphasized in this model, and social network analysis (SNA) is proposed as a tool for identifying key users. The pilot study empirically tested the relationship between the number of key users and that of elicited requirements. The study applied SNA to identify key users (defined as their influence) in “information”, “purchase”, “communication” or “entertainment” networks, and then elicited their requirements of two WIS. The preliminary results demonstrated that the number of key users in “information” dimension was significantly correlated with the numbers of elicited “information” requirements and overall requirements. However, the number of key users in “purchase”, “communication” and “entertainment” dimension had no significant relationships with the number of the elicited requirements. The requirements collected from 20 percent of “key users” accounted for approximate 80 percent of total requirements, similar to the results predicted by Pareto’s rule. In addition, the representativeness of requirements from key users opinions was also tested. Two online communities were designed to explore the relationship between user roles, user involvement and users’ perception towards requirements. And the MANCOVA results showed that user role (with user involvement as a blocking variable) has a major impact on an individual’s perception towards requirements, though the difference varies in a certain way. User involvement has also a determining effect on a user’s perception toward each type of requirements. Managerial implications were also discussed.

對於大量零碎的資料，社會網路分析提供了一個可能的方向，可以更容易 的對個體與整體進行觀察，而得以發掘其中隱藏的資訊。本論文嘗試以我 國政府官員異動資料為一零碎資料的代表，利用社會網路分析做為工具， 提出網路模型以幫助我們分析與觀察其中所隱藏的資訊。利用官員的異動 時間記錄建立網路，實驗的模型共可分為人物共同異動網路、人物共事時 間網路，職務升遷網路，人物共同異動網路部分，將每一人物視為不同節 點，節點間的連結則為兩人共同異動的次數，輔以職務間相關性的關係對 資料中的雜訊進行過濾，人物共事時間網路則以兩人在相關單位共事的時 間長度做為其節點間的連結，職務網路改為以職務做為節點，利用人物的 職務升遷，在前後任職的職務節點間建立連結，對於所建立的各種網路， 再利用社會網路分析中一些性質或指標進行分析。實驗結果顯示本研究所 設計的模型對於觀察人物間相互關係以及不同單位所產生的群體間的關係 有所幫助，並提供對於社會網路分析在類似情境下應用的可能性與限制的 了解。

隨著資訊科技的發達，資訊成長的速度日以倍計，對於大量且片斷的資料，社會網路分析(Social Network Analysis)提供我們可能的研究方法。社會網路主要是由節點以及節點彼此間的連結所形成的網路結構，透過社會網路分析和連結預測理論，我們可以從微觀與巨觀的切入角度，來進行龐大資料量的政府人事異動資料庫進行研究分析。本論文研究，將政府人事異動資料庫中的異動記錄建構為人物與職務兩類不同的社會網路結構，並透過社會網路分析以及連結預測，來發掘人物與不同職務之間的相互影響性，並進一步分析在特定職務的實際接任人選上，實際被影響的因素為何。實驗結果呈現本研究所設計出的模型，對於政府人事異動的互動關係在不同角度的觀察上有所幫助，也從中可以發現在實際接任人選上的考量上，歷任人選的歷任職務有相當程度的影響性，並瞭解社會網路分析與連結預測在實際情境應用下的可能性與限制性。 / Information grows up in very fast way with the advancement in information technology. SNA (Social Network Analysis) provides the possible research ways for the large number of fragmentary information. Social network is the network structure which constructed by the links of each nodes in it. Through SNA (Social Network Analysis) and Link Prediction theory, we can investigate government official's succession database with huge amount of data from micro and macro perspectives. The objective of this study is the construction of two different types of person and position social network structures and the exploration of the interaction between the person and position nodes through link prediction theory. We also discover the impact factors for actual appointee of specific position in further analysis. The study result shows the design model helps us to observe the interaction in government official's succession from different perspectives. We found that is great influence of successive positions of successive candidates in consideration of actual appointee.

隨著網路資訊技術的進步，同時也建構了人與人之間知識傳遞與情感維繫的各種不同社會網路形式與空間，透過瞭解人際之間的社會網路運作，不僅關係個人是否能成功實現目標，亦可協助組織解決問題與意識傳遞及運行。加上近年來「性別主流化」(Gender mainstreaming)政策影響，從過往兩性到現今多元性別的轉變，希望建立尊重多元性別的態度及平等相處的互動。本研究試圖將多元性別族群意識傳遞與社會網路分析技術做結合，以社會網路分析方法，來描述網路上多元性別族群意識傳遞之社會活動的特徵與其意義，對多元性別族群網路使用者的網上集體行為進行剖析，以社會網路分析方法呈現，從人與人的互動分析中，探討多元性別族群意識如何傳遞。並延續看見尊重多元性別做努力，不僅瞭解性別的多樣差異，更重要的是結合資訊管理方式，營造一個資訊管理融合社會多元性別族群友善的環境與資源連結。 / With the advancement of Internet and information technology, various online social platforms have been constructed for interpersonal affiliation and knowledge dissemination. Understanding how the interpersonal social network works helps not only a person fulfill goals but an organization resolve problems and spread its ideas. In recent years, under the influences of the gender mainstreaming policy, the idea of two genders has shifted to the idea of various genders with the hope to encourage a tolerant attitude toward LGBTIQ community and promote equal interaction among all people. The study intends to combine the dissemination of LGBTIQ community awareness and social network analysis. The intention is to depict online dissemination of LBGT community awareness and to dissect the collective behaviors of LGBTIQ community with social network analysis. The analysis of interpersonal interaction is employed to see how the LGBTIQ community awareness has been disseminated. The result not only helps understand differences among genders but also gives insights to know that the most important is to combine LGBTIQ community awareness with information management with the purpose to create a friendlier environment for LBGTIQ community combined with information management.

每一項學術研究進行，其理論基礎都必需要建立於過去已完成的研究之上，因此文獻尋找與探討是進行研究過程非常重要的一個步驟。在數位時代與網際網路的加乘效益之下，改變了過去研究者必需為參考文獻東奔西跑的文獻資料尋找方式，但是卻會造成研究者被許多數位文獻淹沒。借用自網頁分析技術而設計的Google學術搜尋網路工具，能透過已經計算好的文獻權重PaperRank排序使用者所尋找的文獻集合，讓使用者能在數位文獻之中依單篇文獻被引用次數為原則而理出頭緒，但其順序式的排列仍然不能夠揭露出搜尋到的文獻集合裡彼此之間的關聯，其中包括了文獻所使用的關鍵字、作者與參考文獻。為了處理了解文獻中多維度的複雜資料關聯，最好的方式還是依賴人類的視覺化資訊處理能力，特別是當資料量大並且需要在短時間內決策時。 此外使用在文獻分析研究中，學者們使用共同引用(co-citation)、共同作者(co-work)、共同作者引用(co-author)等分析方式，配合延伸自社會網路分析理論中的社會密度(social distance)、關聯層級(social degree)、群(clique)等參數概念，試將複雜的文獻資料有脈絡地按排供參考。僅管此是工作難以機械化且消耗時間的(Börner, Chen , Boyack, 2003)，但是卻能將某一特定領域的發展直覺地呈現出來，如此若能將這些分析方式配合視覺化的呈現，則研究學者便能更進一步了進行大量文獻資料視覺化的分析、探索。 本研究試提出一個新的協助文獻探索平台系統架構，將傳統的文字搜尋轉變為視覺化的資料探索。使用者能透過三種不同的層級的資料：知識本體與關鍵字層、引文網路層及人員網路層，並與呈現的資料互動進一步了解資料間的關聯方式。最後實作視覺化雛型平台，並使用在國家圖書館所提供的博、碩士論文網所提供的論文資料，提供給研究人員探索特定知識領域中新研究方向的探索工具，並能協助研究者能在尚未完瞭解的專業領域之前，能快速地瞭解在該其領域重要文獻的導引平台。 / Paper survey is the most important task for building earnest theories, while researchers conducting academic researches. One must touches the fundamental detail of each theory and track down the develop-path of what achievement have been established by previous researches. Benefit from synergy of information age and document digitalized, it not only reduces the cost of finding reference documents, but also makes researchers suffer from information overwhelming after click single “search it” bottom. Stand in for traditional paper web search methods, new academic paper search technology borrowing from the idea of web search engine calculates the importance of each paper by cited number, and recommends users the most important papers by serial listing. However, serial listing does never spell the relationships of suggesting papers out, but only those results match some specific criteria. Those relationships of papers can be classified into 3 different types: the relations of keywords and references that author used and social relationship of authors like co-author and author co-citation which have been developed to explain the complex citation network structures. Those multi-dimensional relationships are extremely abundant and complex, so there is no better way to deal with but depending on visual data processing within human nature. In this paper, we try to propose a new platform to transform paper search in serial listing, into a visualized explore platform by demonstrating 3 different types of relationship: ontology-keywords, papers-references and personnel-references. End users can fallow the relationships between each difference nodes to explore considerable references, as well as change into different view and interact with existing information by using interactive mechanizes. In order to bring this idea to practical application usage, we build a proto-type platform to show our idea by using data from ETDS (electronic theses and dissertations system) of Ministry of education. We hope sincerely by using this proto-type platform, users can catch the major ideas of specific knowledge domain and researchers can explore acceptable references and even conduct new search topic.

隨著資訊技術的進步，各種史料文本的數位化工作已經處理完成，運用資訊技術於史料文本分析的研究日益增加。本研究以詞頻分析與社會網路分析為主軸，對於古代《易經》爻辭的文字進行多元化的觀察，本研究首先以詞頻分析探討《易經》爻辭字詞頻率的觀察，再利用《易經》爻辭位置資訊建構成各個社會網路結構，對每個社會網路結構運算各項社會網路指標數據，最後將實驗結果與過往《易經》爻辭的論點做印證與對照，期望對於《易經》爻辭之分析，有更多元性的客觀研究觀察。本研究提供了一個分析《易經》爻辭的新面向，也可供未來研究者對於其他古文研究作參考。 / With advances in information technology, digitization of various historical text has been completed.The study of historical text analysis by using information technology is in-creasing daily.In this paper, we used word frequency analysis and social network analy-sis in the I-Ching line statements.First, we used word frequency analysis in I-Ching line statements,using N-gram and TF-IDF technique analysis word frequency.Second, we constructed social network structure by I-Ching line statements position infor-mation,calculating several social network analysis indicator on each network.We com-pared our experiment results with some existing I-Ching theory, expecting to get more objective results and more diverse analysis for the I-Ching line statements. We not only provided a new perspective to study I-Ching line statements but also expected to help other researchers to study different historical text.

Web 2.0的提出，主要的概念是以Web為平台，以「個人」為中心，透過群體智慧的方式來共享與產生知識，例如維基百科、部落格等。部落格提供了個人自由創作與發表文章空間，主要以RSS、Trackback為共有標準，服務提供者可另外加上自訂功能。然而部落格每天所產生的文章量相當龐大，我們是否有辦法在這些文章中，找出符合使用者想看的文章。本研究期望建構一個部落格入口網站，分析目前部落格使用的特徵，比較與目前Web環境差異；引入語意網技術，針對Metadata處理資訊，設計本體論(Ontology)來描述人、文章與標籤之間的關係並建立簡單分類；導入大眾既有經驗與人脈網路建立，觀察社會網路所能提供的貢獻；實作上將透過特徵分析來設計Crawler，自動抓取並解析文章，並建置入口網站，進行資料的分析與驗證，探討加入語意網與社會網路分析的結合所能帶來的效益。 / The Web 2.0 is based on the main concept "individuals" as the center, through the collaborative wisdom to share and to generate knowledge on the Web, such as the Wikipedia, Blog, etc. Blog provides a space for the free creativity and posting articles from individuals. Based on RSS and Trackback service providers can set an additional function. However, the daily amount of articles issued from the Blog is enormous. How can we provide methods for users to find their interesting articles? This study hopes to build the Blog portal and analysis of the current Blog features compared with the web environment. We use semantic web technology and focus on metadata processing. The ontology describes the relationship among persons, articles, tags and a simple categorization. Folks experience and relationship are established and observed with the benefits from social network analysis. In this study, we implement a crawler, and automatically grab and analysis articles. With constructing the portal, we extract information and discuss the benefits of using combination semantic web and social network analysis

隨著資訊科技的發展，數位學習的觀念逐漸興起，在二十一世紀強調知識經濟的今天，自主學習及問題解決能力的養成更顯重要，而藉由網路進行問題導向合作學習，學習者可更方便的透過自主學習方式培養問題解決能力。然而學習者在進行網路合作學習的互動期間會接收到大量來自同儕的資訊，有些學習者常會因為無法判斷資訊的正確性，而無法有效選擇、判斷、分析與整合所獲得的資訊，進而觀望同儕或是意見領袖的意見。因此，本研究利用學習者在問題導向網路合作學習歷程中所產生的社會網路互動資料，利用品質Q函數結合基因算法進行社群探勘，並搭配PageRank演算法找尋出每個社群中的較意見領袖，探討採用教師直接進行資訊傳播的一級資訊傳播模式與透過社群意見領袖進行資訊傳播的二級資訊傳播模式對於學習者的學習成效、社會網路互動及團體凝聚力的影響。此外，也探討採用這兩種資訊傳播模式的不同性別及不同人格特質學習者的學習成效、社會網路互動及團體凝聚力是否具有顯著差異。 研究結果發現：(1)在問題導向網路合作學習環境下，採用發佈訊息給意見領袖之二級資訊傳播模式的實驗組學習者，在學習成效上顯著優於教師透過網站公告之一級傳播模式的控制組學習者；(2)在問題導向網路合作學習環境下，採用發佈訊息給意見領袖之二級資訊傳播模式的實驗組女性學習者，在學習成效上顯著優於透過教師網站公告之一級資訊傳播模式的控制組女性學習者，但兩組男性學習者之間則無顯著差異；(3)在問題導向網路合作學習環境下，採用發佈訊息給意見領袖之二級資訊傳播模式的實驗組學習者，在促進同儕互動成效上顯著優於教師透過網站公告之一級傳播模式的控制組學習者;(4)透過品質Q函數結合基因演算法偵測社群，以及使用PageRank找尋社群意見領袖之方法，能精確的協助教師找到問題導向網路合作學習社群之意見領袖。 最後，根據研究結果，本研究提出教學實施及未來研究方向建議，供後續研究參考以進行更深入的探究。 / The concept of e-learning gradually emerges with the development of information technology. In the 21st century when knowledge economy is emphasized, the cultivation of self-directed learning and problem-solving ability becomes more important. Learners with problem-based cooperative learning through networks can more conveniently cultivate the problem-solving ability with self-directed learning. Nonetheless, learners would receive large amount of peer information during the network cooperative learning interaction; some learners therefore could not effectively select, judge, analyze, and integrated the acquired information by judging the accuracy of information to further observe the opinions of peers or opinion leaders. For this reason, learners’ social network interaction data generated in the problem-based network cooperative learning process are proceeded community mining by combining quality function Q and genetic algorithm, and PageRank algorithm is applied to search for the opinion leader in each community in order to discuss the effects of teachers directly proceeding first-order information communication model and second-order information communication model through community opinion leaders on learners’ learning outcome, social network interaction, and group cohesiveness. Furthermore, the effects of such two information communication models on learning outcome, social network interaction, and group cohesiveness of learners with different genders and personality traits are also investigated. The research findings show (1) learners in the experimental group with second-order information communication model by distributing information to opinion leaders, under the problem-based network cooperative learning environment, significantly outperform learners in the control group with first-order communication model through network announcement on the learning outcome; (2) female learners in the experimental group with second-order information communication model by distributing information to opinion leaders, under the problem-based network cooperative learning environment, present remarkably better learning outcome than female learners in the control group with first-order information communication model through network announcement, while no significant difference appears between male learners in both groups; (3) learners in the experimental group with second-order information communication model by distributing information to opinion leaders, under the problem-based network cooperative learning, notably show better peer interaction effectiveness than learners in the control group with first-order communication model through network announcement; and (4) combining quality function Q with genetic algorithm to detect community and applying PageRank to search for community opinion leaders could accurately assist teachers in finding out the problem-based network cooperative learning community opinion leaders. Finally, suggestions for teaching practice and future research, according to the research results, are proposed in this study for successive research.