Open Access
ARTICLE
Visualization Analysis for Business Performance of Chinese Listed Companies Based on Gephi
1 Institute of Big Data, Hunan University of Finance and Economics, Changsha, 410205, China.
2 Housheng School of International Education, Hunan University of Finance and Economics, Changsha, 410205, China.
3 School of Information Science and Engineering, Central South University, Changsha, 410075, China.
4 School of Finance and Economics, Hunan University of Finance and Economics, Changsha, 410205, China.
* Corresponding Author: Hongzhang Lv. Email: .
Computers, Materials & Continua 2020, 63(2), 959-977. https://doi.org/10.32604/cmc.2020.08619
Received 16 September 2019; Accepted 18 November 2019; Issue published 01 May 2020
Abstract
When conducting company performance evaluations, the traditional method cannot reflect the distribution characteristics of the company’s operating conditions in the entire securities market. Gephi is an efficient tool for data analysis and visualization in the era of big data. It can convert the evaluation results of all listed companies into nodes and edges, and directly display them in the form of graphs, thus making up for the defects of traditional methods. This paper will take all the listed companies in the Shanghai and Shenzhen Stock Exchange as the analysis object. First uses tushare and web crawlers to collect the financial statement data of these companies. And then, uses the Economic Value Added model to calculate the EVA of each listed company and build graph data. Next, import the graph data into gephi to generate the distribution graph of all listed companies’ performance, and summarize the distribution characteristics of business performance. Finally, select a listed company that you want to analyze in detail, using the traditional DuPont analysis method to conduct micro level visualization analysis of the business performance to find the main factors affecting the company’s operating performance. Incorporating gephi into traditional performance analysis methods will make the results of traditional analytical methods more effective and complete.Keywords
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