Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes
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 a...
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Format: | Article |
Language: | English |
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MDPI AG
2022-09-01
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Series: | Entropy |
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Online Access: | https://www.mdpi.com/1099-4300/24/10/1355 |
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author | Hongli Zhou Siqing You Mingxuan Yang |
author_facet | Hongli Zhou Siqing You Mingxuan Yang |
author_sort | Hongli Zhou |
collection | DOAJ |
description | 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. |
first_indexed | 2024-03-09T20:15:36Z |
format | Article |
id | doaj.art-83b5b2576cad4d64992fd07318e4c0a6 |
institution | Directory Open Access Journal |
issn | 1099-4300 |
language | English |
last_indexed | 2024-03-09T20:15:36Z |
publishDate | 2022-09-01 |
publisher | MDPI AG |
record_format | Article |
series | Entropy |
spelling | doaj.art-83b5b2576cad4d64992fd07318e4c0a62023-11-24T00:02:15ZengMDPI AGEntropy1099-43002022-09-012410135510.3390/e24101355Robustness Evaluation of the Open Source Product Community Network Considering Different Influential NodesHongli Zhou0Siqing You1Mingxuan Yang2School of Information, Beijing Wuzi University, Beijing 101149, ChinaSchool of Information, Beijing Wuzi University, Beijing 101149, ChinaSchool of Management, University of Bristol, Bristol BS8 1TH, UKWith 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.https://www.mdpi.com/1099-4300/24/10/1355open source product community networkrobustnessstructural holeopinion leader |
spellingShingle | Hongli Zhou Siqing You Mingxuan Yang Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes Entropy open source product community network robustness structural hole opinion leader |
title | Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes |
title_full | Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes |
title_fullStr | Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes |
title_full_unstemmed | Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes |
title_short | Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes |
title_sort | robustness evaluation of the open source product community network considering different influential nodes |
topic | open source product community network robustness structural hole opinion leader |
url | https://www.mdpi.com/1099-4300/24/10/1355 |
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