A degree centrality in multi-layered social network

TL;DR

This paper introduces a multi-layered degree centrality measure for complex social networks with multiple relationship types, validated through experiments on real Web 2.0 data.

Contribution

It proposes a novel multi-layered degree centrality metric and demonstrates its application on real-world social network data.

Findings

Multi-layered degree centrality provides nuanced network insights.

Experimental analysis on Web 2.0 data validates the measure.

Different degree centralities reveal diverse network characteristics.

Abstract

Multi-layered social networks reflect complex relationships existing in modern interconnected IT systems. In such a network each pair of nodes may be linked by many edges that correspond to different communication or collaboration user activities. Multi-layered degree centrality for multi-layered social networks is presented in the paper. Experimental studies were carried out on data collected from the real Web 2.0 site. The multi-layered social network extracted from this data consists of ten distinct layers and the network analysis was performed for different degree centralities measures.