Network visualization tools can be used to showcase the complexity of any connected data.
During the last years, thanks to the numerous investigations into financial and criminal networks released by various journalist associations, we have seen networks being used more and more for storytelling. Those visual network maps show the main players involved, the connections between them, as well as revealing some interesting insights about the structure of the system.
1. Online Graph Editors
Applications such as Kumu, Graph Commons, Rhumbl or InfraNodus can be used to illustrate the complexity of the relations for almost any topic. All you need to do is to create a graph and start adding the nodes and connections. These apps are much interesting than the standard mind mapping tools, because hey don’t lock you into an hierarchy (there’s no central idea you have to start from). So you can freely build a rhizome of connections. Moreover, you can then use some basic network science tools to analyze and rank the connections and the nodes you have added. For advanced analysis and large graphs, check out Gephi (you will have to install it on your computer though).
2. Data Science
Tools like Graphistry, YWorks and Linkurious are more focused on the data science aspect that can be enhanced using various visualization techniques. InfraNodus also has a data science toolkit that allows you to detect the most influential nodes and apply various network science algorithms, such as community detection and centrality measures.
3. Software Libraries
If you don’t mind to tinker with code, you can set up your own environment and use open-source libraries to visualize and analyze your graph data. The most notable ones are Sigma.Js and Graphology (made by the same team), which can be easily integrated and can read json and gexf file formats.
Using the graph to your right, made with InfraNodus network visualization tool, you can see the most interesting web-based network visualization tools that you can use to visualize data as network graphs. You can also see what data formats (e.g. csv, excel) can be used with these tools with and what kind of operations can be performed on the graphs you build.