A text network visualization in InfraNodus is a representation of text where the words are the nodes and their co-occurrences are the connections between them.
This makes it possible to visualize any text as a network and then apply powerful graph theory algorithms to detect the main topical clusters (word communities based on the co-occurrences) and the most influential concepts (based on their global influence in the network).
This approach has advantages over machine learning models and older approaches such as Latent Dirichlet allocation (LDA) because it provides context-specific information that relates to the very text you're analyzing rather than comparing it to a bigger text corpus. It also enables visual tools to study a discourse to gain additional insight from your text data.
To see InfraNodus in action, add a text, visualize it as a network, and obtain insights in the Analytics panel and from the actual network graph.
To create your first visualization:
1. Go to InfraNodus Apps
Add a New Text app, or open the Menu at the top left and click
+ add new graph link, give a name to your graph, and click
3. You will see an empty page with an input field.
4. Type something in the text input field above, such as:
i am learning something new about text network analysis and right now i'll add my first text graph into infranodus
Alternatively, you can import a file or use an external source (Google, Twitter, Amazon reviews).
You can also copy and paste an existing text you have
5. Then click or tap the
The text graph will be visualized:
As you can see, the main concepts from your statement are visualized as a text network and the Analytics panel on the right provides insight into the main topics identified within (it uses GPT-3 AI).
The statement itself appears above.
6. Add another statement and click Save, for example:
graph visualizations of text help understand the meaning of text, identify the main topics and also see the structural gaps between them
7. You will see a graph visualization of the text you just typed in.
The most influential nodes (words) are shown bigger on the graph.
The different clusters of the nodes (words) that are closer to each other and have distinct colors, indicate the main topics present within the document
8. Use the Analytics panel to obtain insights
The Analytics panel on your right shows you the main topical clusters that emerge in your text as well as the most influential keywords.
You can use these insights to analyze your discourse as you are writing a text and to have an overview of your discourse as it grows bigger and gets more complex.
You can also use Gap Insight panel in Analytics to detect structural gaps (blind spots) in your text and to generate ideas that would connect them using GPT-3.
Please sign in to leave a comment.