An application of event-based dynamic social network analysis for observing political power evolution

• Main Authors: Chuang, Wan Chun, 莊婉君
• Other Authors: Liu, Jyi Shane
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/69682228082221019515

碩士 === 國立政治大學 === 資訊科學學系 === 100 === 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.