政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/54462

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/54462

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政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 > Item 140.119/54462

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題名:	事件導向動態社會網路分析應用於政治權力變化之觀察 An application of event-based dynamic social network analysis for observing political power evolution
作者:	莊婉君 Chuang, Wan Chun
貢獻者:	劉吉軒 Liu, Jyi Shane 莊婉君 Chuang, Wan Chun
關鍵詞:	動態社會網路分析網路分群政府專業團隊政治權力觀察 dynamic social network community detection political community political power observation
日期:	2011
上傳時間:	2012-10-30 11:07:48 (UTC+8)
摘要:	如何從大量的資料中擷取隱匿或不容易直接觀察的資訊，是重要的議題，社會網路提供了一個適當的系統描述模型與內部檢視分析的方法，過去社會網路分析多著重於靜態的分析，無法解釋發生在網路上的動態行為；我們的研究目的是從動態社會網路分析的角度，觀察政治權力的變化，將資料依時間切分成多個資料集，在各個資料集中，利用官員共同異動職務及共事資料建構網路，並使用EdgeBetweenness分群方法將網路做分群，以找出潛在的政治群組，接著再採用事件導向的方法(Event-based Framework)，比較連續兩個時間區間的網路分群結果，以觀察政治群體的動態發展，找出政治群組事件，並將其匯集成政治群組指標，以用來衡量政治群組的變動性及穩定性。我們提供了一個觀察政治權力變化的模型，透過網路建立、網路分群到觀察網路動態行為，找到不容易直接取得的資訊，我們也以此觀察模型解決以下問題：(1)觀察部門之接班梯隊之變化，(2)觀察特定核心人物之核心成員組成模式，(3)部門專業才能單一性或多元性之觀察。實驗結果顯示，利用政治群組事件設計的政治群組指標，可實際反應政府部門選用人才的傾向為內部調任或外部選用。 Extracting implicit information from a considerable amount of data is an important intelligent data processing task. Social network analysis is appropriate for this purpose due to its emphasis on the relationship between nodes and the structure of networked interactions. Most research in the past has focused on a static point of view. It can`t account for whatever action is taking place in the network. Our research objective is to observe the evolution of political power by dynamic social network analysis. We begin by creating static graphs at different time according to the synchronous job change between the government officials or the relationship between the government officials whom work in the same government agency. We obtain political communities from each of these snapshot graphs using edge betweenness clustering method. Next we define a set of evolutionary events of political communities using event-based framework. We compare two consecutive snapshots to capture the evolutionary events of political communities. We also develop two evolutionary political community metrics to measure the stability of political communities. We propose a model of observing the evolution of political power by three steps－network construction, community identification and community evolution tracking. The approach is shown to be effectual for the purposes of: (1) finding succession pool members in government agencies, (2) observing the inner circle of a leading political figure, (3) measuring the specialized degree of government agencies. Experiments also show that our community evolution metrics reflect the tendency of whether a government agency conducts internal succession or outside appointment.
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Zäıane, "Community Evolution Mining in Dynamic Social Networks," Procedia - Social and Behavioral Sciences, vol. 22, pp. 49-58, 2011. [31] C. Tantipathananandh, T. Berger-Wolf, and D. Kempe, "A framework for community identification in dynamic social networks," Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 717-726, 2007. [32] J. Travers and S. Milgram, "An experimental study of the small world problem," Sociometry, vol. 32, pp. 425-443, 1969. [33] S. Wasserman and K. Faust, Social Network Analysis Methods and Applications. New York : USA, 1994. [34] D. J. Watts, Six Degrees: The Science of a Connected Age 2004. [35] M. Zhang, "Social Network Analysis: History, Concepts, and Research " in Handbook of Social Network Technologies and Applications, B. Furht, Ed., ed: Springer US, 2010, pp. 3-21.
描述:	碩士國立政治大學資訊科學學系 98971003 100
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0098971003
資料類型:	thesis
顯示於類別:	[資訊科學系] 學位論文

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