- Volume 10 Issue 1
Nowadays various public data have been serviced to the public. Through the opening of public data, the transparency and effectiveness of public policy developed by governments are increased and users can lead to the growth of industry related to public data. Since end-users of using public data are citizens, it is very important for everyone to figure out the meaning of public data using proper visualization techniques. In this work, to indicate the significance of widespread public data, we consider UN voting record as public data in which many people may be interested. In general, it has high utilization value by diplomatic and educational purposes, and is available in public. If we use proper data mining and visualization algorithms, we can get an insight regarding the voting patterns of UN members. To visualize, it is necessary to measure the voting similarity values among UN members and then a social graph is created by the similarity values. Next, using a graph layout algorithm, the social graph is rendered on the screen. If we use the existing method for visualizing the social graph, it is hard to understand the meaning of the social graph because the graph is usually dense. To improve the weak point of the existing social graph visualization, we propose Friend-Matching, Friend-Rival Matching, and Bubble Heap algorithms in this paper. We also validate that our proposed algorithms can improve the quality of visualizing social graphs displayed by the existing method. Finally, our prototype system has been released in http://datalab.kunsan.ac.kr/politiz/un/. Please, see if it is useful in the aspect of public data utilization.
Supported by : 차세대융합기술연구원
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