社会网络数据的可视化

吉林大学学报(信息科学版) ›› 2015, Vol. 33 ›› Issue (5): 584-.

社会网络数据的可视化

朱琪1, 于济坤1, 王明德2, 丁洪超1, 贺嘉楠1, 隋鹏1, 董立岩1

1. 吉林大学计算机科学与技术学院, 长春130012; 2. 中国建设银行股份有限公司审计部, 北京100033

收稿日期:2015-06-21 出版日期:2015-09-30 发布日期:2015-12-30
作者简介:朱琪(1991—), 男, 江苏靖江人, 吉林大学硕士研究生, 主要从事数据挖掘研究, (Tel)86-15143089558(E-mail)zhuqi13@ mails. jlu. edu. cn; 董立岩(1966—), 男, 长春人, 吉林大学教授, 博士生导师, 主要从事数据挖掘研究, (Tel)86-18604315166(E-mail)dongly@ jlu. edu. cn。
基金资助:
国家青年自然科学基金资助项目(61300145)

Data Visualization for Social Network

ZHU Qi1, YU Jikun1, WANG Mingde2, DING Hongchao1, HE Jianan1, SUI Peng1, DONG Liyan1

1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;2. Audit Department, China Construction Bank Corporation, Beijing 100033, China

Received:2015-06-21 Online:2015-09-30 Published:2015-12-30

摘要/Abstract

摘要：

为直观地分析社会群体网络, 观测社会群体行为, 提出了社交网络数据的可视化分析方法。该方法将社会关系网络描绘成由点和线组成的图, 再对图形中的节点分布位置、节点的大小以及点线密度等进行有效分析。运用在线社会网络数据可视化分析技术, 结合python 可视化与python 科学计算技术, 增强了网站的吸附性, 获得了较好的用户体验。

关键词: 社交网络, 数据可视化, 社会群体行为, python 科学计算

Abstract:

In order to analyze the social group network visually, and to make accurate observation of the socialgroup behavior, the social network analysis method named social network data visualization is presented. Thesocial relation network was described as composed of point and line chart. Moreover, we make effective analysisto the node distribution location, the size of the graphics and dotted line density. Using the online visualizationanalysis technology for social network data, combined with the python visualization and python scientificcomputing technology, the system enhances the adsorption of websites, and it has gained a good user experience

Key words: social network, data visualization, social group behavior, python scientific computation

中图分类号:

TP301

朱琪1, 于济坤1, 王明德2, 丁洪超1, 贺嘉楠1, 隋鹏1, 董立岩1. 社会网络数据的可视化[J]. 吉林大学学报(信息科学版), 2015, 33(5): 584-.

ZHU Qi1, YU Jikun1, WANG Mingde2, DING Hongchao1, HE Jianan1, SUI Peng1, DONG Liyan1. Data Visualization for Social Network[J]. Journal of Jilin University(Information Science Ed, 2015, 33(5): 584-.