In this brief tutorial, we introduce the basic workflow you can use to get an overview and insight into your data using the network graph generated with InfraNodus.
After you watch it you'll be able to apply the same approach to your own data to not only get an overview of discourse but also to generate new interesting ideas. You can use your own text or any existing discourse (e.g. Google or AI-generated facts).
Video Tutorial:
Text Graph Workflow Tutorial:
Step 0: Create a New Graph and Choose the Editor Mode.
There are 3 options available:
1. Analyze a Text — upload or copy and paste an existing text, detect the main topics and the relations between them. This is the option we demonstrate in the workflow below.
2. Develop an Idea — start with an idea, a research question, or an abstract. Then use the AI assistant to explore it further. If you decide to choose this option, please, go to 🎥 Live AI Ideation Workflow: Develop Ideas using GPT-3 and Text Visualization
3. Explore a Topic — start with a keyword or a topic, and either import the Google search results to understand the context around or use the live AI ideator to generate interesting facts, then add them to the graph. If you want to try this option, go to 🎥 Explore a Topic using GPT-3 AI and Text Data Network Visualization
Below we will demonstrate how you can proceed if you choose the first option: Analyze a Text. You can also use this approach below with the other two options once you populate your graphs with content, in order to analyze the discourse generated. For instance, an easy way to populate your graph with a content is to use the Google import app.
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Step 1: Add a Text.
Copy and paste a text into the editor or import an existing text to visualize it as a graph: a PDF or a text document, Google search results, or Twitter conversations around a certain hashtag.
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Step 2. Get an overview and identify the top influential nodes and the topical clusters.
The graph will show you the main terms in your discourse, the main topics, and how they are related (methodology). We found that visualizing a text as a graph helps think more in terms of connections (research).
The bigger nodes on the graph have higher influence in the discourse network (based on betweenness centrality). The nodes that have the same color belong to the same topical cluster — it means they are better connected together than with the rest of the network. You can view this information in the Analytics > Topic panel.
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Step 3. Use the graph to find the relevant concepts in texts (zooming in).
Click on the nodes on the graph you find interesting to find out what other nodes / words they are connected to and to reveal the context where they appear. This enables you to read the text in a non-linear way focusing on the patterns that emerge, rather than the chronological narrative.
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Step 4. Delete the obvious nodes.
Some words may seem obvious to you. Like "machine learning" in the context of "AI". So you can select those on the graph and remove them temporarily to see what's hiding behind those terms (see the image below). You can always get them back into the graph if you click the Undo button (next to the lock button, which permanently removes the stopwords).
Step 5. Check out the Insights.
This is located in the Analytics panel (right bottom). The Insight panel shows you the structural gap: the parts of the discourse that are relevant on their own but are not yet connected. Bridging them together will usually lead to potentially interesting and creative ideas.
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Step 6. Use the AI Insight Helper Panel.
Look at the AI Insight panel and check if there are any interesting ideas proposed there. You will find it at the bottom of the screen. It analyzes the structure of the discourse to discover the blind spots in your ideas. It then recommends the research questions that bridge those blind spots, helping you generate new interesting insights using GPT-3 AI.
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Step 7. Add Your Ideas
Once you get new ideas, you can:
- add a new text (you can use use the "Ideas" tag to separate your ideas from the content you generated earlier)
- add some notes about the graph in the Info menu on the left (in this case, your notes will not be visualized on the graph, they are for your internal reference only).
- click Interpret to start interpreting the data you are seeing — this will create a new graph that will be juxtaposed on top of the existing one, so you can separate your ideas from the original content.
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Step 8. Compare Your Graphs or Tagged Statements.
You can also compare the graph to another graph (or the statements that belong to the different categories in your current graph) to see what the common ideas or how they are different.
Use the buttons on the left menu to do that:
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Step 9. Share your research
by downloading the graph as a PNG / SVG image, or getting a URL link and posting it on the social media using #infranodus to promote your work and ideas.
Learn how to do that in this article: How to Share Your Graphs
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Step 10. Reiterate.
Get back into the overview, use the graph to find new patterns and connections again. If at any point you like the graph you are seeing, you can always save its current version (the auto-save only works for temporary browser sessions and it doesn't save all the data).
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Graph Exploration — InfraNodus Workflow Schema
Here is the ideal graph exploration workflow that you can use with your texts and files.
(please, click on the image to view it in full size)
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