centrality

Comparative analysis of networks' centrality measures with ANOVA

This study introduces the GDK method, combining Global Structure Model (GSM), Degree Centrality (DC), and K-shell decomposition (Ks), to assess node significance in networks.  In comparison to traditional metrics (Degree Centrality, Betweenness Centrality, and Closeness Centrality), GDK is evaluated across three network types: social (Email), scientific (Netscience), and technological (Router).  Analysis of Variance (ANOVA) and Kendall's correlation show that GDK consistently achieves higher correlation in ranking nodes, making it a more reliable tool.  By integrating l

Zealots' effect on opinion dynamics in complex networks

In this paper, we study zealots' effects on social networks.  Our social network is based on scale-free networks using Barabasi–Albert method and random networks using Erdős–Rényi method.  We used a pre-studied modified Voter model that includes zealots, individuals who never change their opinions.  We chose prominent individuals (i.e.