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
AI Qualitative Data Analysis Software
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.
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:
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.comYou 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.
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.
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.
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.
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:
Workflow Example: Qualitative Analysis of Interviews
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Real Graph Examples
Start Using InfraNodus
Sign up for an account now, so you can get insight using this tool for your own data and texts.
How Qualitative Analysis with InfraNodus Works
InfraNodus represents your text as a network of concept or a knowledge graph. We then apply various graph science metrics to identify topical clusters, which help reveal the main themes in your data.
Here is how it works:
1. Add Any Text or Import Data
Add any text, customer reviews, 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).
2. Visual Theme Clustering
The network will then be generated from the text or data you added. 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.
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 tag clouds.
3. Detect Insights & Blind Spots
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.
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)
Various Other Use Cases
The best way to use InfraNodus is to identify structural gaps in texts or any connected data, so that you know what is missing and how to fulfil it. Some areas of application include:
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Sentiment Analysis of Product Reviews (topic modeling)
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Text Mining with Networks (discourse structure analysis)
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Visual Google Search (a great way to get an overview of any topic)
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Network Analysis (community detection and node ranking algorithms)
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Visual Arts and Music (sculpt your thoughts and play music with graphs)
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Search Engine Optimization / SEO (finding the untapped keywords)
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Scientific Research (generate insight from your writing)
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.
Advanced Account
saving €204 or 35%
- 14-day free trial
- everything on the Basic +
- API access
- Dedicated support
- 2 Mb per upload
- 5 Mb per PDF upload
- Extended data import quotas
- 100 GPT-4 credits / hour
- Live graph updates (max 5)
- Commercial use
Basic Account
saving €84 or 35%
- 14-day free trial
- Community support
- Full graph analytics
- Chrome / Firefox extension
- Obsidian graph view plugin
- Import data from web sources
- Max 40 imports per source
- 300 Kb per file upload
- 1Mb per PDF upload
- 40 GPT-4 AI credits / hour
- Personal / Academic use
Premium Account
- 14-day free trial
- everything on Advanced +
- API integration support
- Training: 1 hour / month
- 10 Mb per upload
- 50 Mb per PDF upload
- Max import quotas
- 500 GPT-4 credits / hour
- Live graph updates (max 20)
- Fast-track required features
InfraNodus vs. Other Tools
Tools such as MaxQDA, Nvivo, 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.
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:
Qualitative Analysis FAQ
Check out our FAQ, so you can see how text networks and knowledge graphs can enhance your qualitative analysis workflows.
How do I import qualitative data, cluster it, and turn it into insights?
You can upload the texts as PDFs or text files or import your data as a CSV or JSON file for granular control over categories and themes that you've already identified. Then you can use the AI topical clustering algorithm in InfraNodus to automatically identify the main themes with text network analysis and write them down in Project Notes as well as tag statements by the themes they belong to. It is also possible to use the interactive graph to peel off the top layer of concepts and topics to expose what's hiding underneath and reveal deeper layers of meaning. You can learn more in the Qualitative Analysis of Interviews, Open-Ended Survey Responses and Customer Feedback support article.
How to read and interpret text networks and knowledge graphs?
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
How to use the knowledge graph to explore your data?
Network graphs are great for non-linear reading. Look at the graph, find the part you like, click on the nodes or topical clusters, and you'll see the excerpt of your original data that contains this exact combination. More on Nonlinear Reading
How is InfraNodus different from other text analysis software?
InfraNodus is a visual tool that allows you to explore any textual data as an interactive network. This helps you uncover the relational patterns you would not have otherwise seen and also explore the text in a non-linear way, exploring emerging relations and patterns. More on Visualizing PDFs