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題名 基於社會網路分析連結預測理論之政府官員職位與職務歷程影響研究
Government post candidacy analysis based on link prediction in social network
作者 黃俊生
貢獻者 劉吉軒
黃俊生
關鍵詞 社會網路分析
連結預測
政府官員異動
日期 2009
上傳時間 4-Sep-2013 17:10:37 (UTC+8)
摘要 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.
參考文獻 [1] 摘自總統府公報網站資料, Internet URL: http://www.president.gov.tw/2_report/subject-01.html,2009.
[2] 翁嘉緯 , 《以型態辨識為主的中文資訊擷取技術研究》, 國立政治大學資訊科學系碩士論文,2003。
[3] 林岡隆 ,《政府官員異動之社會網路分析》,國立政治大學資訊科學系碩士論文,2009。
[4] 顏秋來 ,《政務官與事務官體制運作之研究》,國家菁英,第二卷第一期,頁21-28,
[5] 林嘉誠 ,《政務首長的流動分析-2000.5-2007.5》,國家菁英,第三卷第四期,頁1-28,2007。
[6] 胡龍騰 ,《政黨輪替前後高階行政主官流動之比較》,國家菁英,第三卷第四期,頁31-42,2007。
[7] A.R. Radcliffe-Brown. "On Social Structure. Journal of the Royal Anthropological Institute". 70:1-12, 1940.
[8] D. Liben-Nowell and J. Kleinberg. "The Link Prediction Problem for Social Networks". in the proceedings of Journal of the American Society for Information Science and Technology, vol. 58, no. 7, pp. 1019–1031, 2007.
[9] E.P.H. Zeggelink, F.N. Stokman, and G. G. van de burt. "The emergence of groups in the evolution of friendship networks". Journal of Mathematical Sociology. 21:29-55, 1996.
[10] G. Jeh and J. Widom. "Simrank:a measure of structural-context similarity". in KDD`’02: Proceedings of the eighth ACM SIGKDD international conference
on Knowledge discovery and data mining, (New York, NY, USA), pp. 538–543,
ACM Press, 2002.
[11] J.A.Barnes, "Class and Committees in a Norwegian Island Parish".Hum Relations, 7(1):39-54, 1954.
[12] J. Moody, and D.R. White. "Structural Cohesion and Embeddedness:A Hierarchical Concept of Social Groups". American Sociological Review. 68(1):103-127, 2003.
[13] J. Scott. "Social Network Analysis:A HandBook". Sage, Newbury Park, CA, 1992.
[14] L.C. Freeman. "The Development of Social Network Analysis:A Study in the Sociology of Science". Empirical Press, Vancouver, CA, 2004.
[15] M.E.J. Newman, M.Girvan. "Finding and evaluating community structure in networks".Phys. Rev. E 69:026113, 2004.
[16] M.E.J. Newman. "Modularity and community structure in networks". Proc. Natl. Acad. Sci. USA. 130:8577-8582, 1006.
[17] M.E.J. Newman. "The structure of scientific collaboration networks". Proceedings of the National Academy of Sciences USA, 98:404-409, 2001.
[18] R.S. Burt. "Structural Holes. The Social Structure of Competition". Harvard University Press, Combridge MA, 1992.
[19] R. Cross, A. Parker, and S.P. Brogatti. "A bird`s-view:Using socical network analysis to improve knowledge creation and sharing". Knowledge Directions. 2(1):48-61, 2002.
[20] S.P. Borgatti, M.G. Everett. "Network analysis of 2-mode data". Social Network, 19(3):243-269, 1997.
[21] S. Wasserman and K. Faust. "Social Network Analysis Methods and Applications". Combridge University Press, New York, USA, 1994.
[22] V. Kerbs. "The Social Life of Routers". Internet Protocol Journal. 3(December):14-25, 2000.
描述 碩士
國立政治大學
資訊科學學系
92753035
98
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0927530351
資料類型 thesis
dc.contributor.advisor 劉吉軒zh_TW
dc.contributor.author (Authors) 黃俊生zh_TW
dc.creator (作者) 黃俊生zh_TW
dc.date (日期) 2009en_US
dc.date.accessioned 4-Sep-2013 17:10:37 (UTC+8)-
dc.date.available 4-Sep-2013 17:10:37 (UTC+8)-
dc.date.issued (上傳時間) 4-Sep-2013 17:10:37 (UTC+8)-
dc.identifier (Other Identifiers) G0927530351en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/60263-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 92753035zh_TW
dc.description (描述) 98zh_TW
dc.description.abstract (摘要) 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。
zh_TW
dc.description.abstract (摘要) 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.
en_US
dc.description.tableofcontents 第 一 章 緒 論 ...................1
1.1 研究背景 ...................1
1.2 研究資料 ...................2
1.2.1 總統府公報 ...................2
1.2.2 政府官員異動資料庫 ...................3
1.3 研究動機與目的 ...................4
1.4 本研究之貢獻 ...................5
1.5 論文架構 ...................5
第 二 章 文獻探討 ...................7
2.1 社會網路與分析 ...................7
2.1.1 起源與發展 ...................7
2.1.2 基本定義 ...................9
2.1.3 網路分析層次 ...................10
2.1.4 網路性質分析指標 ...................12
2.1.4.1 節點(NODE)相關分析指標 ...................12
2.1.4.2 節點集合(NODE SET)相關分析指標 ...................14
2.1.4.3 整體網路(NETWORK)相關分析指標 ...................16
2.2 連結預測 ...................18
2.2.1 基本概念與定義 ...................18
2.2.2 相關演算法 ...................19
2.3 小結 ...................24
第 三 章 人物異動網路之建置與系統架構 ...................25
3.1 人物異動網路建置 ...................25
3.2 研究方法分析 ...................27
3.3 系統架構 ...................30
3.3.1 系統概述 ...................32
3.3.2 NETWORK MODULE ...................33
3.3.3 SIMRANK ALGORITHM MODULE ...................37
3.3.4 PREDICTION LIST MODULE ...................40
第 四 章 實驗設計與分析評估 ...................47
4.1 實驗資料 ...................47
4.2 實驗設計模式 ...................50
4.3 實驗數據結果 ...................51
4.3.1 相似度遞減係數討論 ...................51
4.3.2 遞迴次數實驗討論 ...................52
4.3.3 訓練年限長度實驗討論 ...................72
4.4 結果分析與討論 ...................75
4.4 實驗總結 ...................81
第 五 章 結論與未來研究方向 ...................82
5.1 研究結論 ...................82
5.2 未來研究方向 ...................84
參考文獻 ...................86
附錄A 四大職務類別職務接替人選推薦列表 ...................88
zh_TW
dc.format.extent 1641184 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0927530351en_US
dc.subject (關鍵詞) 社會網路分析zh_TW
dc.subject (關鍵詞) 連結預測zh_TW
dc.subject (關鍵詞) 政府官員異動zh_TW
dc.title (題名) 基於社會網路分析連結預測理論之政府官員職位與職務歷程影響研究zh_TW
dc.title (題名) Government post candidacy analysis based on link prediction in social networken_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] 摘自總統府公報網站資料, Internet URL: http://www.president.gov.tw/2_report/subject-01.html,2009.
[2] 翁嘉緯 , 《以型態辨識為主的中文資訊擷取技術研究》, 國立政治大學資訊科學系碩士論文,2003。
[3] 林岡隆 ,《政府官員異動之社會網路分析》,國立政治大學資訊科學系碩士論文,2009。
[4] 顏秋來 ,《政務官與事務官體制運作之研究》,國家菁英,第二卷第一期,頁21-28,
[5] 林嘉誠 ,《政務首長的流動分析-2000.5-2007.5》,國家菁英,第三卷第四期,頁1-28,2007。
[6] 胡龍騰 ,《政黨輪替前後高階行政主官流動之比較》,國家菁英,第三卷第四期,頁31-42,2007。
[7] A.R. Radcliffe-Brown. "On Social Structure. Journal of the Royal Anthropological Institute". 70:1-12, 1940.
[8] D. Liben-Nowell and J. Kleinberg. "The Link Prediction Problem for Social Networks". in the proceedings of Journal of the American Society for Information Science and Technology, vol. 58, no. 7, pp. 1019–1031, 2007.
[9] E.P.H. Zeggelink, F.N. Stokman, and G. G. van de burt. "The emergence of groups in the evolution of friendship networks". Journal of Mathematical Sociology. 21:29-55, 1996.
[10] G. Jeh and J. Widom. "Simrank:a measure of structural-context similarity". in KDD`’02: Proceedings of the eighth ACM SIGKDD international conference
on Knowledge discovery and data mining, (New York, NY, USA), pp. 538–543,
ACM Press, 2002.
[11] J.A.Barnes, "Class and Committees in a Norwegian Island Parish".Hum Relations, 7(1):39-54, 1954.
[12] J. Moody, and D.R. White. "Structural Cohesion and Embeddedness:A Hierarchical Concept of Social Groups". American Sociological Review. 68(1):103-127, 2003.
[13] J. Scott. "Social Network Analysis:A HandBook". Sage, Newbury Park, CA, 1992.
[14] L.C. Freeman. "The Development of Social Network Analysis:A Study in the Sociology of Science". Empirical Press, Vancouver, CA, 2004.
[15] M.E.J. Newman, M.Girvan. "Finding and evaluating community structure in networks".Phys. Rev. E 69:026113, 2004.
[16] M.E.J. Newman. "Modularity and community structure in networks". Proc. Natl. Acad. Sci. USA. 130:8577-8582, 1006.
[17] M.E.J. Newman. "The structure of scientific collaboration networks". Proceedings of the National Academy of Sciences USA, 98:404-409, 2001.
[18] R.S. Burt. "Structural Holes. The Social Structure of Competition". Harvard University Press, Combridge MA, 1992.
[19] R. Cross, A. Parker, and S.P. Brogatti. "A bird`s-view:Using socical network analysis to improve knowledge creation and sharing". Knowledge Directions. 2(1):48-61, 2002.
[20] S.P. Borgatti, M.G. Everett. "Network analysis of 2-mode data". Social Network, 19(3):243-269, 1997.
[21] S. Wasserman and K. Faust. "Social Network Analysis Methods and Applications". Combridge University Press, New York, USA, 1994.
[22] V. Kerbs. "The Social Life of Routers". Internet Protocol Journal. 3(December):14-25, 2000.
zh_TW