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iGraph: Also good for large graphs and if you prefer R over Python for your data analysis and have a solid knowledge of R then you may want to use iGraph.NetworkX: An active community and terrific if you have some Python knowledge. If you have a large dataset (>100,000 nodes say) then this is a great place to start as many of the computationally intensive metrics now make use of sparse matrices.There is also a version called Pajek-XXL which is specifically designed for very large graphs - if you have a network with millions of nodes and no programming skills and would like to analyse it then this wouldn't be a bad starting place. Pajek: At a high-level, not too dissimilar to Ucinet in that it is quite strong on analytics but relatively weak on visualization.It also requires Windows for installation so Mac users have to be creative by using an emulator for example. it can calculate both the common metrics as well as some quite arcane metrics but it's not great at turning those results into a well presented visualization. However, it is quite weak on visualization in my view (really thinking about its cousin Netdraw here), i.e. It's very strong on analytics with a large number of metrics. Ucinet: In my experience Ucinet is most widely used in academic circles.In my experience it's primarily used in the biology domain but can certainly be used outside of it and is capable of producing high quality visualizations. Cytoscape: There is actually both a desktop version as well as a javascript version for developers (see cytoscape.js).The main advantage of NodeXL though is neither in its visualization or analysis functionality but rather in it's data collection - it interfaces with the Twitter API nicely for example and many of the use cases for NodeXL involve the visualization and analysis of social media data in my experience It also interfaces directly with the SNAP library for analysis which gives it access to a nice set of efficient algorithms for metric calculations. It doesn't have all of the flexibility of Gephi in terms of visualization but can produce some quality visualizations.

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NodeXL: NodeXL is an Excel add-in so you will need Excel to use it which is a bit of a limitation for Mac users for example.

but it's a stronger tool for visualization than analysis. It does have the ability to calculate a few of the more common metrics such as degree, centrality, etc. It can also handle relatively large graphs - the actual size will depend on your infrastructure (particularly RAM) but you should be able to go up to 100,000 nodes without a problem. It's strength is that it is able to produce very high quality visualizations. Gephi doesn't require any programming knowledge.

Gephi: Probably the most popular network visualization package out there.

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You cannot download any crack or serial number for DataThief on this page. Typically, you scan a graph from a publication, load it into DataThief, and save the resulting coordinates, so you can use them in calculations or graphs that include your own data DataThief III is a program to reverse engineer data points from a graph.