Generate Insight using
Text Network Analysis

InfraNodus is a network thinking tool for reading and writing.

You can use it with your ideas, raw text, Google search results, PDFs, CSV, spreadsheets, Obsidian, Roam Research, Twitter, Evernote, RSS feeds and more. Analyze any discourse, your own writing, customer reviews, scientific papers. Find the structural gaps and generate new ideas using the built-in GPT-3 AI by OpenAI.
InfraNodus Text Network Visualization App

Visualize any Text or Data as a Network,
Perform Text Analysis

Use powerful network analysis algorithms, AI plug-ins, and data mining tools to get a new perspective and insights.

Live Text Input
and Data Import

Write or import a text, PDF, Evernote notes, Google search results, Tweets, RSS news feeds, Gephi graphs, CSV files...

Text Mining and
Topic Modeling

Using network analysis tools we will identify and visualize the main nodes, keywords, topics, clusters, and sentiment.

Network Analysis
and Visualization

Your data is represented as a beautiful network graph, which can be used as an heuristic device to generate new ideas.

AI-based GPT-3
Ideas Generator

Discover the most interesting research questions and ideas based on OpenAI's GPT-3 and network analysis.


Use English, German, French, Spanish, Portugese, Russian, Swedish, Italian, Dutch, Japanese, Chinese.

Fully Shareable

You can link to your graphs, embed them to your site, save in gexf, png, csv formats. Full data export with metrics.

Private by Default

All your data is private by default and you can export and erase it anytime. On-premise installation possible.

Interactive Graphs

You have full control over the graphs: move the nodes, delete them, make connections, filter, select the relevant parts.

InfraNodus Workflow


You can use standard text, hashtags or file import to add your data.

Text to network graph visualization

Reveal the patterns in your data using network analysis.

Topic modeling and text mining using text network analysis

Use the interactive graph to find the most relevant excerpts.

Get the relevant excerpts using the graph

Find the structural gaps so you know where the new ideas are hiding.

Structural holes in knowledge graphs generate new ideas

Use OpenAI's GPT-3 and network structure insights to generate research questions and innovative ideas.

Use OpenAI's GPT-3 to generate research questions and innovative ideas for your discourse

See What InfraNodus Can Do

InfraNodus can be used for text mining, sentiment analysis, social and discourse network analysis, and creative writing.

Use Case: Text Mining and Topic Modeling

Problem: What are the main topics inside a text?

The current solutions are either too simplistic or too technically challenging.

Solution: Topic modeling based on text network analysis and visualization.

InfraNodus will represent the text as a network and use powerful graph analysis algorithms to identify and visualize the main keywords, topics, and their relations.

Learn More    Try It Out

Use Case: Discourse Structure and Bias Analysis

Problem: How to identify the level of diversity and bias in a text or a network?

Suppose that we want to study the current discourse on coronavirus. What are the main topics and how diverse is the media coverage of this subject? What is the level of urgency?

Solution: Represent the text as a network and measure the diversity and bias of the graph structure.

InfraNodus represents any text as a network, so you can get insights about the structure of the discourse.

Based on the graph's modularity and distribution of influence across the different communities, we can measure the diversity of the discourse stucture and estimate its bias.

Watch the Video    Try It Out


Use Case: Creative Writing & Idea Generation

Problem: How to generate new ideas for your writing or at a brainstorming session?

Whether you are brainstorming, doing research or writing you may experience writer's block or simply get stuck for new ideas.

Solution: InfraNodus will represent your text as a network providing a visual overview and helping you find the gaps where the new ideas are hiding.

Our studies have shown that network representation of text encourages one to think in terms of connections, helping you make the new links between the different parts of your text and make your discourse more coherent.

You will also be able to see the structural gaps in your writing: that's where the new ideas our hiding.

Learn More    Try It Out

Use Case: Sentiment Analysis of Open Survey Customers Answers

Problem: Need to know what your customers think?

Open survey answers are hard to analyze. Positive / negative is not enough and tag clouds lose out the context.

Solution: Find the patterns in their open survey answers using network graphs.

With InfraNodus your customers' feedback will be visualized as a word graph where the words used in the same answer are connected.

This representation will reveal the patterns and context in your customers' answers, so you will see the main topics that appear in their feedback as well as the hidden relations between them that can't be uncovered by other tools.

Read the Case Study    Try It Out

Use Case: Coming Up with Ideas for a New Article

Problem: Need to develop a discourse on a certain topic?

The difficult part is to begin, to gather everything together and to start writing.

Solution: InfraNodus live text visualization and insight recommender system.

Start writing your ideas and InfraNodus will visualize them as a graph. The Insight Recommender system will show the connections between your ideas and reveal the structural gaps — recommending you the interesting questions to ask to develop your discourse further.

Tutorial    Sign Up to Try

Use Case: Brainstorming and Generating Ideas

Problem: Have an idea you'd like to develop?

Traditional brainstorming tools make it hard to come up and connect ideas.

Solution: Find the patterns in your thought and make your ideas more coherent.

With InfraNodus you coan just start writing your thoughts into the graph, so you can gradually see how they connect.

The graph representation will provoke a higher level of coherency in your thinking and you can use it to ask yourself unexpected questions that will connect the ideas that have not been connected before.

Watch the Demo    Sign Up to Try

Use Case: Rhizomatic Mind Mapping

Problem: Build a map of your knowledge to understand it better

Standard mind maps start with a central idea, plus it's easy to get lost in them as they grow.

Solution: Using InfraNodus to build rhizomatic mind maps with advanced graph analytics.

With InfraNodus you can just start writing your ideas as the connections betwen them will be visualized automatically.

You can use #hashtags to add the specific nodes and use our advanced graph analytics based on network theory to reveal the most important clusters of ideas and the most influential nodes in your thought.

Quick Tutorial    Sign Up to Try

Use Case: Analyzing Your RoamResearch (or Evernote) Notes

Problem: Struggling to make sense of your notes

Even if you make the links between them manually, once their number grows it becomes hard to understand what they're about.

Solution: Use InfraNodus to visualize the conenctions between them and find the most relevant ideas.

You can import your RoamResearch, Evernote or any other notes into InfraNodus to visualize the connections between the notes and also the content within them.

Using advanced graph analytics you will get a detailed overview of your ideas and reveal the structural gaps between them — where the potentially interesting new ideas might be hiding.

RoamResearch / Obsidian Tutorial    Evernote Tutorial    Sign Up to Try



See a Demo Graph     Create Your Own




Other Network Graphs Use Cases

Text graphs made from research articles, essays, speeches, texts, and PDF files.
Subscribers can upload their own files, MD archives, PDFs, TXT and CSV files.


Mindmap Examples

Mind maps and concepts maps made using InfraNodus text-to-graph mindmapping app.
Use #hashtags or [[wiki-links]] to create your nodes as your write or use our automatic text recognition system.


Start Using InfraNodus

Sign up for an account now, so you can get insight using this tool for your own data and texts.

How Text Network Analysis Works

Network analysis and graph visualization help you cope with the informational overload and make sense of data.

Here is how it works:


1. Add Any Text or Data

You can use this approach for your research, creative writing, marketing feedback study, SEO purposes, news analysis, etc.

Add any text (speech-to-text available), notes, or import your Gephi graph, Evernote data, Twitter feed, or Google search results snippets.

The text is converted into a graph where the words are the nodes and the co-occurrences are the connections between them, so you can see all your disjointed bits and pieces of data at once, as a big picture.

More in our Whitepaper
Create a Text Network Graph

2. Get a Visual Overview

The network will then be generated from the text or data you added. The most influential words in the graph (nodes with the highest betweenness centrality) are shown bigger, while the words (nodes) that occur more often together are aligned into topical clusters and have distinct colors.

The graph will show you not only the main topics and the most influential terms, but also the relations between them, making it a much better visual summary tool than the traditional tagclouds.

Overview Data with Text Network Visualization

3. Generate Insight

InfraNodus will identify the structural gaps in the network: parts of the graph that could be connected but are not.

It will propose you the different ways how you can bridge these gaps to produce insight and generate new ideas.

You can also export your data as a CSV file (with the InfraNodus insights) for further analysis or to use as a training data for your neural network applications.

Generating Insight with Structural Gaps

Methodology, Whitepaper, Citations:

To learn more about the algorithms used in InfraNodus and for citations, please, refer to this peer-reviewed paper:

Paranyushkin, D (2019). InfraNodus: Generating Insight Using Text Network Analysis, Proceedings of WWW'19 The Web Conference, (ACM library, PDF).

If you want to know more about the algorithms used, here is the first paper we published on the subject:

Paranyushkin, D (2011). Identifying the pathways for meaning circulation using text network analysis, Nodus Labs. (Google scholar)

Become a Supporter!

InfraNodus is open-source software and is developed without external funds or investors. We develop and maintain this tool and the associated research based on your contributions only. We believe it is a working model for crowdfunded software made by users for users.

You can support our work if you become a subscriber and get access to the cloud version or if you become our patron on Patreon. Enterpise, government, and educational versions are also available.

Pricing Options

InfraNodus and the associated research is supported solely by our subscribers and patrons, that's why we ask for a subscription payment.

We don't accept any investments or government grants, helping us keep this tool affordable, independent, and free from the corporate and ideological agendas.

About InfraNodus: Our Philosophy

Gregory Bateson coined a beautiful term: "ecology of the mind". What is a mind that is ecological? It has the ability to have an overview, but it can also zoom into any idea. It embraces diversity, but it can also obsess over one thing when needed. It can discover the obvious, but it can also reveal the things that are hidden and ponder the gaps that have not yet been bridged. Focused and, yet, adaptive. Rational and poetic.

InfraNodus is a tool that is developed to help you think this way. It is made to promote ecological dynamics and diversity on the cognitive level. InfraNodus visualizes and analyzes ideas as a network, revealing the relations and patterns within them, so you can understand the dynamic complexity of how knowledge evolves and explore the nuances of meaning.

We believe that it is especially important today to make this kind of instrument available to everybody. That's why we develop InfraNodus so that it can be accessible to everyone, solely thanks to our users' monthly contributions and based on their feedback.

We also provide an API to ensure that this way of thinking is available not only to humans, but also to other machines, applications, AI programs, and machine learning algorithms.

If you like our cause, please, sign up for an account and give it a try, support us on Patreon, or simply let us know that it resonates. Your feedback is our fuel.

Dmitry Paranyushkin, the founder


Cognitive Variability: Panarchic Thinking with InfraNodus

Panarchic thinking

InfraNodus is especially designed to promote cognitive variability. Too often people get stuck with a certain idea or a pattern of thinking. InfraNodus can be used as a mind antivirus against obsessive loops — biased ideas, mundane patterns, totalitarian thinking, propaganda, and narrow-mindedness — proposing a kind of thinking that is pan~archic: spanning a range of states and modalities.

Using text network analysis, InfraNodus identifies the structure of the discourse through the measures of network modularity, distribution of influence, and narrative variability. It then uses its algorithms and AI to steer this structure towards a more adaptive and open state.

If the discourse is too biased towards a certain idea, InfraNodus will steer it towards diversification. If the discourse is too dispersed, InfraNodus will steer it towards more focus.

In plain terms, if InfraNodus was a conversational partner (which you can experience with the AI Chat App), it would support a conversation for some time, but then also switch the subject and go on a tangent towards a different topic. After some time, it will bring the conversation back to the central ideas, stay there for a while exploring the nuance, and then shift the subject to a new topic again.

Cognitive polysingularity: network variability dynamics.

In the technical terms, it works the following way:

1→2 #bias #growth #vector #exponent:
If the discourse is too biased towards a certain group of concepts (stage 1 to 2 on the graph), InfraNodus will highlight the less represented ideas and propose you to explore them and to connect them (50%/50% explore / focus ratio and 50%/50% zoom in / out ratio at the stage 2).

2→3 #focus #saturation #plateau:
This will bring the discourse towards a focused state (stage 2 to 3). Higher connectedness, focus on multiplicities, increasing the scale, zooming out, linking ideas more than exploring (80% to 20%).

3→4 #focus #conservation #intensification:
Now we can start zooming in again, decreasing the scale, connecting ideas within a smaller area, deepening the focus inside the existing structure (stage 3 to 4 on the graph).

4→5 #diversification #assimilation #release:
Once the discourse has become even more "focused" (stage 4 to 5), InfraNodus will also suggest to develop the specificities, zoom in further, go bigger scale, and, thus, reduce (global) focus and increase the proportion of exploration again (to 20%).

5→6 #diversification #redirection #fractalization:
It will then propose to diversify the discourse by zooming out and exploring more clusters, developing each of them further (stage 5-6: moving between locally related ideas and also jumping across the structural gaps in the graph).

6→7 #dispersion #reogranization:
At some point, we shift towards dispersion by giving more weight to the exploration process, rather than focus (state 6-7: dispersion).

7→8 #dispersion #reset:
Once the scale is large enough, we zoom into the small scale again while exploring until we find a new concept we'd like to develop (stage 7-8).

8→1 #bias #genesis:
We then focus on it and develop it further again (stages 8 to 1).




InfraNodus is used by researchers, writers, marketing professionals, corporations, and NGOs — Greenpeace, Procter & Gamble, and others. Here's what some of our supporters have to say:

Technical Support

Check out our support pages, so you can see how to create the new network graphs, how to read and interpret them, how to discover the hidden patterns in your data and share the results of your research.

1. How to Create a New Graph

The most basic way to create a new graph is to use the hashtags. Each hashtag is a node, their co-occurrence is the connection between them. You can also use normal text to build your text graphs automatically. More on Creating the Graphs

2. How to Read and Interpret Network Visualization

Studies have shown that diagrams and especially network representation of data makes you think more of connections in your data. You can identify the main elements as well as the relations between them and — most importantly — discover the gaps in your knowledge using the graphs. More on Reading the Graphs

3. Find the Right Excerpt in Text

Network graphs are great for non-linear reading. Look at the graph, find the part you like, click on the nodes, and you'll see the excerpt of your original data that contains this exact combination. More on Nonlinear Reading

4. How to Import Text and PDF files

You can import and visualize your text files or PDF documents. In order to do that, just upload the file and InfraNodus will do the rest. More on Visualizing PDFs