Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes
Hongli Zhou1, Siqing You1, Mingxuan Yang2
1School of Information, Beijing Wuzi University, Beijing 101149, China.
Entropy (Basel, Switzerland)
|July 8, 2023
Summary
Open source product communities (OSPCs) rely on robustness for stable development. This study introduces a new method to identify influential nodes, improving network robustness analysis and revealing the impact of user behavior on community stability.
Area of Science:
- Complex Systems
- Network Science
- Social Computing
Background:
- Open source product communities (OSPCs) are vital in internet technology.
- Network robustness is crucial for OSPC stability.
- Traditional node importance metrics (degree, betweenness) are insufficient for OSPCs.
Purpose of the Study:
- To develop an improved method for identifying influential nodes in OSPCs.
- To analyze the impact of influential node loss on OSPC network robustness.
- To investigate the effect of user following behavior on network robustness.
Main Methods:
- Complex network modeling to construct a typical OSPC network.
- Integration of network topology characteristics for improved node identification.
- Simulation of node loss strategies to assess network robustness changes.
Main Results:
- The proposed method effectively distinguishes influential nodes compared to traditional metrics.
- OSPC network robustness significantly decreases with influential node loss (structural holes, opinion leaders).
- User following behavior substantially alters network robustness.
Conclusions:
- The developed robustness analysis model and metrics are feasible and effective for OSPCs.
- Identifying and protecting influential nodes is critical for OSPC stability.
- Understanding user following dynamics is essential for maintaining network integrity.
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