Social Network Analysis

Yuh-Wen Chen
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Abstract

Social network analysis (SNA) is an attractive problem for a long time when social communities were popular since 2010. Scholars like to explore the meaning behind the numerous interactions generated at these social media sites. The primary and essential issue of SNA is to monitor, estimate, and engage the potential influencers who are most relevant and active to network. If we can analyze the social network this way, business enterprises could use minimal efforts to sustain the activity of influential users, improve sales, and enhance their reputations. In this chapter, a research framework based on multiple-criteria decision making (MCDM) is proposed. The authors will show how scholars could use dynamic self-organizing map (SOM) based on multiple-objective evolving algorithm (MOEA) and static weighted influence non-linear gauge system (WINGS) to analyze a social network. Finally, comparisons are made between the innovative approaches and the methods in tradition.
社会网络分析
社交网络分析(Social network analysis, SNA)是自2010年社交社区兴起以来一直备受关注的问题。学者们喜欢探索这些社交媒体网站上产生的众多互动背后的意义。SNA的主要和基本问题是监测、估计和吸引与网络最相关和最活跃的潜在影响者。如果我们能以这种方式分析社交网络,商业企业可以用最小的努力来维持有影响力的用户的活动,提高销售额,提高他们的声誉。本章提出了一个基于多准则决策的研究框架。作者将展示学者如何使用基于多目标进化算法(MOEA)的动态自组织地图(SOM)和静态加权影响非线性测度系统(WINGS)来分析社会网络。最后,对创新方法与传统方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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