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Network analysis is a method used in various disciplines, and it is typically employed to examine relationships within a network structure. These disciplines include social sciences, information science, humanities, epidemiology, communication, transportation, and many more. Essentially, network analysis involves the study of a structure that displays relationships (often referred to as "edges" or "links") between a set of objects (usually called "nodes").

The most commonly used tools, software, and programs for network analysis are as follows:

  Gephi: Gephi is an interactive and visual network analysis software. It visualizes network structures and allows for various types of analysis.

  Pajek: It is widely used for analyzing large networks. It has the capability to work with large datasets.

  Cytoscape: This is commonly used for biological network analysis, including gene regulation, protein-protein interactions, and it can also be used for general network analysis.

  NodeXL: It is an Excel add-on for network analysis. It's useful for visualization and basic analysis.

  UCINet: This is popular for social network analysis and supports various data formats.

  R and Python: These two programming languages have a wide range of libraries for network analysis. Particularly, the igraph library in R and networkx in Python are popular choices for network analysis.

  NetLogo: It's a platform used for agent-based modeling, including network modeling, particularly for modeling social phenomena.

   GUESS: This is a network analysis tool that focuses on visualization and graph exploration.

Introduction to Network Analysis

Network ties: reciprocity, transitivity, homophliy

Network groups: communities, permutation tests, QAP & netlm

Exponential random graph models (ERGM)

Martin Grandjean's YouTube Channel

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