Python for Graph and Network Analysis by Mohammed Zuhair Al-Taie & Seifedine Kadry

Author:Mohammed Zuhair Al-Taie & Seifedine Kadry
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

4.12 Social Network Analysis Modeling Tools

Social network analysis modeling tools are software packages that can be used to identify, represent, analyze, and visualize social networks. Examples include Pajek: software for analysis and visualization of large networks, UCINET, StOCENT, Gephi, Network Workbench, and NodeXL.

Special-purposes SNA modeling tools can be used to carry out particular analysis tasks such as the identification of subgroups, knowledge networks, hidden populations, kinship networks, and structural networks. Examples include NEGOPY, InFlow, and SocioMetric LinkAlyzer. Some modeling tools have programming utility such as NetworkX, JUNG, iGraph, Prefuse, and SNAP.

Because most of the concepts and techniques that social network analysis is based on are taken from mathematical graph theory, it is indispensable to spend some time briefing the main concepts in graph theory.

The main goal of SNA is to find local and global patterns, identify influential actors, and investigate network dynamics. Therefore, SNA is involved in the analysis of ties between people, organizations, and even countries.

Throughout the following three chapters, we will go through three levels of analyses including finding key players in the social network at the ego (individual) level, detecting distinctive communities in networks at the group level, and finally implementing cohesion analyses at the network level.

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