What tools are used for analysing web graphs?

Tools used for analysing web graphs include Gephi, NodeXL, Cytoscape, Graph-tool, NetworkX, and Pajek.

Gephi is an open-source software for visualising and analysing large networks graphs. It allows users to explore data through a variety of layouts and adjust visual properties like colours, size and labels. Gephi also provides advanced metrics to measure the network's topology and distribution.

NodeXL is a free, open-source template for Microsoft Excel that allows you to display, analyse, and collect complex network graphs. It's particularly useful for those who are already familiar with Excel and want to extend its functionality to include network analysis. NodeXL can handle both directed and undirected graphs, and it provides a variety of layout algorithms to help visualise the data.

Cytoscape is another open-source software platform for visualising complex networks. It's particularly well-suited for analysing biological data, but it can be used for any type of network data. Cytoscape supports a wide range of network types, including directed, undirected, weighted, and unweighted graphs.

Graph-tool is a Python module for manipulation and statistical analysis of graphs. It provides efficient algorithms for a variety of tasks, including graph drawing, centrality measures, clustering, and community structure detection. Graph-tool is particularly useful for those who want to integrate network analysis into larger Python projects.

NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. It provides data structures for graphs, digraphs, and multigraphs, as well as algorithms designed for these data structures. NetworkX is highly flexible and can handle graphs of any size and complexity.

Pajek is a program for analysing and visualising large networks. It's particularly well-suited for social network analysis, but it can be used for any type of network data. Pajek provides a variety of algorithms for analysing the structure of networks, as well as tools for visualising the results.

All these tools have their own strengths and weaknesses, and the choice of tool often depends on the specific requirements of the project. However, they all provide powerful capabilities for analysing and visualising web graphs.