Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes

稳健性(进化) 计算机科学 中间性中心性 复杂网络 分布式计算 数据挖掘 计算机网络 数学 中心性 统计 生物化学 化学 万维网 基因
作者
Hongli Zhou,Siqing You,Mingxuan Yang
出处
期刊:Entropy [Multidisciplinary Digital Publishing Institute]
卷期号:24 (10): 1355-1355 被引量:1
标识
DOI:10.3390/e24101355
摘要

With the rapid development of Internet technology, the innovative value and importance of the open source product community (OSPC) is becoming increasingly significant. Ensuring high robustness is essential to the stable development of OSPC with open characteristics. In robustness analysis, degree and betweenness are traditionally used to evaluate the importance of nodes. However, these two indexes are disabled to comprehensively evaluate the influential nodes in the community network. Furthermore, influential users have many followers. The effect of irrational following behavior on network robustness is also worth investigating. To solve these problems, we built a typical OSPC network using a complex network modeling method, analyzed its structural characteristics and proposed an improved method to identify influential nodes by integrating the network topology characteristics indexes. We then proposed a model containing a variety of relevant node loss strategies to simulate the changes in robustness of the OSPC network. The results showed that the proposed method can better distinguish the influential nodes in the network. Furthermore, the network’s robustness will be greatly damaged under the node loss strategies considering the influential node loss (i.e., structural hole node loss and opinion leader node loss), and the following effect can greatly change the network robustness. The results verified the feasibility and effectiveness of the proposed robustness analysis model and indexes.
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