Text Network Analysis and Data Visualization Tutorials
InfraNodus is an AI-powered network analysis and visualization platform that can be used to better understand the relations within your data.
All the users get access to the applications which customize the tool for a specific use case. Below we offer some tutorials that you can use to start exploring your data using this tool:
Choose an Application to Learn More about Each Use Case Scenario:
These applications can be used to fulfil concrete use cases. For example, an aspiring researcher looking for an interesting topic to explore; or a marketing specialist looking for an onoccupied niche in the public discourse.
The most interesting way to use InfraNodus is to get the insight about the dynamic nature of any structure. The elements that are sustainable and strong, the weaker parts, and the structural lacks. We can then use this knowledge to better understand the phenomena we are studying or to promote a certain action in relation to this structure, which, in turn, promotes a certain dynamics we're interested in.
Some of the areas of application that we've seen our users do include:
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Scientific Research
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Search Engine Optimization (SEO)
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Creative Writing
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Marketing Research
On the website of Nodus Labs, the company that created InfraNodus tool and these apps, you can find a collection of use cases and research that make use of network analysis approach:
Read the Case Studies
User's Manual: InfraNodus as Ideas Generation Tool
The most basic use case of InfraNodus is to generate new ideas. You can do this on your own with free writing or using your notes from before.
Simply add your ideas into the graph, using a simple text, if you just want to be writing, or using #hashtags and @mentions if you want to construct a mental map or a graph. Then watch the patterns emerge and the software start giving you the Insight advice and tips on what you think of next.
Hint 1: Use Text-to-Graph Input
The basic advantage of InfraNodus is its state-of-the-art text-to-network conversion system. You can use text to quickly build graphs which you can then use to reflect on and analyze the text itself.
Every word is visualized as a node and every co-occurrence is the connection. Gradually the patterns emerge that show the most connected clusters of words together.
To be more precise you can use #hashtags and @mentions when you enter the information. Each #hashtag is a node and it connects to the other #hashtag, which is next to it. You can also link the #hashtags to a specific node using the "mention" @ prefix. E.g. #apples and #oranges are @fruits.
You can, of course, also import your data from any external text, a PDF file, Evernote, Twitter or Google, Gephi, and many other formats.
Hint 2: Use the Graph as an Heuristic Thinking Machine
Once you generate a text network graph, you can get insights both qualitatively, just looking at the graph, and quantitatively — using the Analytics panel. For example:
