InfraNodus: Network Analysis and Visualization Tool
Uncover Hidden Patterns, Main Clusters, and Nodes in Any Network with AI-Powered Insights and Graph Theory
Examples of Text Network Graphs Made with InfraNodus:
Create Your Own Text Graphs
Sign up for an account now, so you can try how it works. We offer a 14-day free trial, so you don't have to pay anything if InfraNodus doesn't live up to your expectations.
How InfraNodus Network Analysis & Visualization Tool Works
1. Visualize a network graph and apply graph theory metrics
Using our peer-reviewed methodology, we visualize a network graph and identify the main clusters using Louvain community detection algorithm, apply Force Atlas layout, and rank the nodes by betweenness centrality. This helps you get a structural overview of the network.
More on the Methodology in our Whitepaper
2. Identify the structural gaps and optimize network structure
Based on the insights about the network's structure, InfraNodus can identify the structural gaps and suggest different ways to optimize the network, depending on the objective. For instance, if the goal is to improve propagation, small-world, scale-free structure would be preferable. This could be achieved by targeting the gaps between clusters and generating new connections between them.
3. Use interactive graph to explore the network and generate insights
You can select the nodes and remove them from the graph to see what the network would look like without them (all analytics will be recalculated). This is especially useful for testing the network's resilience and uncovering hidden patterns that are not visible in the original network.
Our Methodology and 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, 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)
We also invite you to consult our research on network optimization, bias detection, and text network analysis applications:
See the Nodus Labs website and our Support Portal.
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Pricing Options
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
Most of the other text analysis tools are either too general, lack interactivity, or have too many complex settings. InfraNodus helps you use the network graph as an heuristic device to explore the underlying structure and generate interesting insights based on the structural data.
without InfraNodus
- Provide generic insights
- Have complex settings
- Do not offer AI insights
- Lack interactivity in the graph
- No API or too complex to access
with InfraNodus
- Help find structural gaps
- Ready-made settings template
- Built-in AI to generate insights
- The graph is fully interactive
- Has a public API and built-in GraphRAG
Testimonials
InfraNodus is used by researchers, writers, marketing professionals and corporations. Here's what some of our supporters have to say:
Frequently Asked Questions
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. What are the different types of networks?
A network's type will define how resilient or adaptive it is, how well information can be propagated through it, how susceptible it may be to an attack. Learn more about network types
2. How do you calculate community structure of a network?
We use the Louvain community detection algorithm to identify the main clusters in your network based on the nodes' co-occurrence. We also apply Force-Layout algorithm to position the nodes in a way that makes the graph's community structure more readable. More on network community structures
3. How do you calculate a node's influence?
We use betweenness centrality to calculate a node's influence. This measure shows how instrumental a node is to connecting the different clusters in a network, how often it acts as a bridge between them. More on Betweenness centrality
4. Can I generate a graph using AI?
Yes, you can generate a graph using our built-in AI. For example, you can ask InfraNodus to generate a graph of the main concepts related to "machine learning" and to then use this graph to explore the topic in more detail More on Generating knowledge graphs with AI