Your browser doesn't support javascript.
loading
Robustness of open source community multi-project knowledge collaboration network based on structural hole theory.
Lei, Shaojuan; Wang, Chenzhi; Zhang, Taoge; Liu, Xinhua.
Afiliação
  • Lei S; Nuclear and Radiation Safety Center, MEP, Beijing, China.
  • Wang C; Nuclear and Radiation Safety Center, MEP, Beijing, China.
  • Zhang T; Nuclear and Radiation Safety Center, MEP, Beijing, China.
  • Liu X; Nuclear and Radiation Safety Center, MEP, Beijing, China.
PLoS One ; 19(1): e0292444, 2024.
Article em En | MEDLINE | ID: mdl-38165961
ABSTRACT
Nodes in the structural hole position play a key role in the multi-project network of the open source community (OSC). This paper studies the robustness of this network based on structural hole theory. First, a semantic-based multi-project KCN is constructed, and four node types are identified knowledge contribution nodes, knowledge dissemination nodes, structural hole nodes (SHNs) and opinion leader nodes. Second, a robustness analysis model of the edge failures of these four key nodes is constructed. Third, a simulation test is conducted on the proposed model using empirical data from the Local Motors multi-project OSC. The results show that the KCN has the lowest robustness when facing the edge failure of opinion leader nodes, followed by knowledge dissemination nodes, knowledge contribution nodes, SHNs and random nodes. The edge failure of opinion leader nodes causes the lowest network robustness because of the propagation effect of these nodes. Additionally, SHN failure has only a small initial impact on connectivity, whereas knowledge collaboration efficiency decreases rapidly (i.e., the edge failure of SHNs causes the network to enter a state of high connectivity and low efficiency). The proposed model can be used to provide comprehensive and targeted management guidance for OSC development.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China
...