AI Qualitative Data Analysis with Knowledge Graphs

Analyze interviews, focus groups, and survey responses visually. Detect patterns, code qualitative data, and find content gaps using AI.



 
Watch an Introduction
 

 
 
Text mining and topic modeling using network analysis

Automatic Coding with Interactive Knowledge Graphs

Instead of requiring manual coding, InfraNodus converts your qualitative data — interviews, focus groups, open-ended surveys, fieldnotes — into an interactive knowledge graph where the concepts are the nodes and their co-occurrences are the connections. Topical clusters and patterns emerge directly from the structure of the data itself.

You can use the graph to manually explore the data and themes and peel off the top layer of concepts to reveal deeper meaning.

1. Add Survey Answers and Questionnaire Responses

Copy and paste or upload interviews, survey responses, reviews, files, or CSV spreadsheets.

2. Use Text Mining and Networks to Visualize the Main Themes

Our powerful NLP and text network analysis algorithms will visualize the main themes and the relations between them.

3. Perform Sentiment Analysis on Your Questionnaire Data

Reveal the main topics in the positive / negative responses and the keywords they are associated with.

4. Use AI & Graphs to Reveal Gaps and Generate Ideas

Detect structural gaps in the survey responses and use the built-in AI to generate new ideas that bridge those gaps.



Multilingual

Perform analysis in multiple countries and languages: English, German, French, Dutch, Spanish, Italian, Chinese, Japanese.

Fully Shareable

You can download hi-res copies of the graphs to add to a presentation. You can also export a URL or an embed code to add it to your website.

Compare Documents

You can compare the different groups of responses to see how they overlap or how they differ. Use the filters to reveal the missing parts.

Advanced Analytics

Use the network analysis metrics to reveal the insights that are not available with traditional tools, such as structural gaps.





Multiple Import Sources


You can ingest data from multiple sources and formats automatically, no need for a scraper anymore. Here are some of the most popular ones, you can also use the API and MCP to connect to your own data sources:

 

PDFs & Markdown

Multiple text files import: txt, pdf, md.

CSVs & Spreadsheets

Import by columns, advanced filtering

Plain Text

Copy and paste any text in real time

Google & SEO

Search results, Scholar, related search queries


YouTube

Transcripts, comments, search results

Websites

Scrape whole websites, URLs, and sitemaps

Amazon

Product search results and customer reviews

News & RSS

RSS feeds, latest news, XML files





MCP Server and n8n Node for Your Favorite LLM


You can use InfraNodus in your favorite LLM client like Claude or ChatGPT via our MCP server. This lets you save your data in InfraNodus with structured knowledge graph insights and then explore them in your favorite LLM.

https://mcp.infranodus.com

You can also connect InfraNodus to n8n via our official n8n node.






Qualitative Analysis Workflow:

 

Import your open survey responses and questionnaire data, detect the clusters of main topics inside. Unlike other tools, InfraNodus shows you the results in context (e.g. "battery" connected to "life") and also reveals the main topical clusters: themes that naturally emerge in your particular data set.

Topic modeling of customer review data

Use the advanced Google AI model to reveal the sentiment in your responses. Filter the results by sentiment to see what the negative respondents are talking about. Filter by positive / negative sentiment to reveal the themes that emerge in each sentiment.

Sentiment analysis of customer reviews

Use the integractive graph to find the parts of the respondents' discourse that are relevant. Peel off the top layer of concepts to reveal deeper layers of meaning.

Get the relevant excerpts using the graph

Identify the structural gap (the ideas that are not yet connected) and use the built-in GPT AI to generate ideas that would fulfil this gap.

Identify the structural gap - what ideas are not connected yet





Step by Step Open Survey Responses Analysis Tutorial:

Check out this help article from our support center, which demonstrates a workflow for performing open survey data analysis:


Survey Responses Data Analysis

 

Sign Up to Try with Your Data

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:

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1. Add Any Text or Data

Add any text, field notes, survey responses, questionnaire data, or import your text files, CSV spreadsheets, Twitter feed, Google search results, RSS feeds, and more.

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. See more on the methodology below (with a citation for academic publication).

More in our Whitepaper
Create a Text Network Graph
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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 influence based on betweenness centrality measure) 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.

The concepts that tend to occur in the same responses will belong to the same topical clusters and reveal themes in your data, which you can use for manual or automatic coding.

Overview Data with Text Network Visualization
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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 do that yourself using the intuitive knowledge graph interface or use built-in AI to generate ideas for you.

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

Generating Insight with Structural Gaps



Our Methodology in Detail

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, www.infranodus.com (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)


Sign Up for a Free 2-Week Trial

Discover the power of network analysis and AI-augmented knowledge graphs for qualitative research.

Pricing Options: Free 14-Day Trial

Your support is what makes it possible for us to develop this tool. All quotas are per each text. There is no limitation on the number of texts you can process every month. Prices do not include VAT for EU private customers.

Lock in current prices for life and save up to 35% (€100-€200) on our annual plans.

Monthly Annual Save up to 35%

 

 
Sign Up for a Free 14-Day Trial

InfraNodus vs. Other Tools

Tools such as MaxQDA and AtlasTI are unable to understand underlying relationships in your data. InfraNodus provides a unique approach to text analysis that reveals hidden patterns and insights in your data.

without InfraNodus

Legacy Research Tools

  • Require manual coding
  • Limited interactivity
  • No topical clusters
  • No content gap detection
  • Simplistic visualizations
  • Rudimentary AI functionality
  • No sentiment analysis
  • No API available

AI Chatbots

  • Use bulletpoints and long text
  • Provide generic responses
  • Black-box approach hides reasoning
  • No graph, no deeper understanding of context

with InfraNodus

Text Network Analysis

  • Automatically reveals themes in your data
  • Explore data manually with interactive graphs
  • Identifies topical clusters
  • Content gap detection
  • State-of-the-art interactive graph
  • Built-in AI for in-depth analysis
  • Built-in sentiment analysis
  • Provides API access and LLM workflows

AI Knowledge Graph

  • Reveal patterns in your data
  • Original insights from the structure
  • Interactive graph shows you what's happening
  • GraphRAG finds gaps in your knowledge

 

 

About InfraNodus: Our Philosophy

One of the most important skills for any organization is the ability to listen. InfraNodus is designed to provide a deeper insight into a public discourse about your organization, revealing high-level ideas as well as hidden insights. It can also identify whatever it is that is missing, helping you generate innovative ideas from listening to what the others say about you.

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. Rational and poetic.

InfraNodus is a tool that is developed to help you think and listen in this way. It is made to promote ecological dynamics and diversity on the cognitive level. InfraNodus visualises and analyses 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.

Panarchic thinking


How does InfraNodus achieve that? It uses a combination of network theory and social science. In fact, InfraNodus' special sauce is to apply social network analysis techniques to discourse analysis. Once you start seeing the words as people and their co-occurrences as the connections, you can build social networks of concepts, in order to identify the most influential ideas. Then you can target those influential concepts and ideas to connect your own discourse to that of a market.

This can be especially useful for studying open-ended survey responses and questionnaire data. With InfraNodus, you can understand both the general picture and the hidden nuance, because you can use the network visualization to explore the data to the fullest extent.



InfraNodus can also be particularly helpful for removing cognitive bias and helping you see the nuances nobody else does. Most of the time, people think that if they know the main keywords they get an idea, but this idea is usually superficial. InfraNodus, on the other hand, allows you to get rid of the first, obvious layer of ideas and get to the depths of a discourse, revealing both high-level ideas and the insights hidden within or at the periphery of a discourse.

It also uses multiple tools from social sciences to help you identify the most effective entrance points into any discourse, which can be particularly helpful if you want to be heard in a crowded space. The insights obtained using InfraNodus can be really helpful for bringing innovative products to the market, the sort of things that are hard to promote using conventional tools.

If you would like to learn more about how InfraNodus works, you can sign up for an account and give it a try or learn more about our approach in the About InfraNodus section where we showcase some of the cutting-edge algorithms and frameworks we use. You may also be interested to find out more about the competitive intelligence approach.

Dmitry Paranyushkin, the founder


 

 


 

 

Testimonials

InfraNodus is used by researchers, writers, marketing professionals and corporations. 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