Revealing the Non-Obvious: Graph Exploration Workflow

Suppose you visualized a discourse, you have a good overview of what it's about, and now you want to dig deeper into the analysis and find out the parts that may be not so evident, but still relevant. 

Let's use our original example: a graph of Google search results for "text network analysis" query. We already got a good overview of what this discourse is about and now want to dive deeper into it.
  

General Workflow to Discover the Relevant Information:

1. Look beyond the obvious. The best way to start is to remove what you already know from the picture to see what are the relevant parts of the network behind it.

In order to do that, click on the nodes on the graph to select them and then click the trash button to remove them: 

2. Once you do that, the node will be removed from the graph, all the metrics will be recalculated, so you will see the influential terms and topics that were connected to the nodes you removed:

3. You can then repeat the process or get the nodes you deleted back into the graph: either by clicking on the nodes themselves or the Undo button:

4. Alternatively, you can also use the Reveal Non-Obvious function:

Go to the Analytics Panel (bottom right) and click "remove influential" button under the most influential nodes to see what's hiding behind them:

5. We will see that once the influential terms are removed, they are added into the list of stopwords, together with text, network, analysis. The graph statistics is recalculated and now some new influential words come up:

social    order    visualize

6. Let's explore the context: click on the "social" or "order" and then "Show Statements" menu in the top left to see the context where these terms are used:

We will find a paper that is talking about combining text mining and social network analysis to identify new potential biomarkers for breast cancer — something that we would probably not normally see if we just skimmed through the Google search results.

7. Once you understand the context, you can remove these nodes from the graph (Trash button next to them).

8. We can then continue exploring more specific contexts around these topics if we click on the different nodes, learn about the context, reiterate. For example, further clicking on terms we get to the "analyze" and "paper" nodes. If we click on them we find an interesting case study of using the text network analysis approach for analyzing academic papers, which indicates an interesting application of this method:

9. You can get the nodes you removed using the "Reveal Non-Obvious" function back into the graph if you click on the undo button next to it:

10. When you are finished, you can keep the graph at its current state or get all the nodes you deleted back into the graph if you either click on each node red tag or on the Undo button next to them:

Try this yourself with this public demo graph:

https://infranodus.com/support/google_tna?background=default&most_influential=bc&maxnodes=150&stopwords=text+network+analysis