Dr. Jie Hua Profile

Dr. Jie Hua

at Shaoyang Univ

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Proceedings Article | 27 November 2019 Paper

Adopting centrality measure models in visualized financial datasets

Jie Hua, Guohua Wang, Youquan Xu

Proceedings Volume 11321, 1132103 (2019) https://doi.org/10.1117/12.2537801

KEYWORDS: Social networks, Visualization, Data modeling, Visual process modeling, Visual analytics, Analytics, Social network analysis, Data processing

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The financial data is complex to analyse due to its complicated relationships and multiple attributes. Centrality measure models from the SNA (Social network analysis) can show the most critical variables in a network, and graph layouts can be produced to represent not only data networks but also the relations among data entries. To the best of our knowledge, there is no work that has been tried on the Australian stock market based on the combination of those two methods mentioned above so far. This study adopts centrality measure methods and a graph drawing algorithm (force-directed) to offer users big pictures and detailed views, comes with ranking factors based on weighted degree, pagerank and eigenvector metrics. The outcomes show that the methodology can produce clear graph layouts of the stock’s social network, identify the central stocks (represent through features such as node colour and size) and the business sectors they belong to. This study may assist stakeholders with grasping deep insight from the complex financial datasets, and another angle of view to adjust future investments accordingly.

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