A parameterizable influence spread-based centrality measure for influential users detection in social networks
作者：
Highlights：
• We propose a new centrality measure based on influence spread models.
• This measure accepts different parameters regarding the neighborhoods activation.
• We apply two experiments with 257 executions using different parameter settings.
• For well-connected networks, the depth level of neighborhoods is critical.
• For loosely connected networks, the initial activation probability of the neighbors is critical.
摘要
•We propose a new centrality measure based on influence spread models.•This measure accepts different parameters regarding the neighborhoods activation.•We apply two experiments with 257 executions using different parameter settings.•For well-connected networks, the depth level of neighborhoods is critical.•For loosely connected networks, the initial activation probability of the neighbors is critical.
论文关键词：91D30,05C22,05C21,Centrality,Influence spread,Social influence,Social network
论文评审过程：Received 4 April 2022, Revised 14 September 2022, Accepted 16 September 2022, Available online 22 September 2022, Version of Record 28 September 2022.
论文官网地址：https://doi.org/10.1016/j.knosys.2022.109922
