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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600624/ https://www.ncbi.nlm.nih.gov/pubmed/37420375 http://dx.doi.org/10.3390/e24101355 |
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author | Zhou, Hongli You, Siqing Yang, Mingxuan |
author_facet | Zhou, Hongli You, Siqing Yang, Mingxuan |
author_sort | Zhou, Hongli |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-9600624 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96006242022-10-27 Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes Zhou, Hongli You, Siqing Yang, Mingxuan Entropy (Basel) Article 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. MDPI 2022-09-24 /pmc/articles/PMC9600624/ /pubmed/37420375 http://dx.doi.org/10.3390/e24101355 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhou, Hongli You, Siqing Yang, Mingxuan Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes |
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 | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600624/ https://www.ncbi.nlm.nih.gov/pubmed/37420375 http://dx.doi.org/10.3390/e24101355 |
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