• Posted by | April 3, 2026

    Landscape Reading Model — Text Network Representation

    How do we perceive a text when we read it? The answer to this question can help us understand how attention functions and identify various strategies to enhance our writing. Additionally, it can inspire new methods of reading that increase engagement and accessibility. In this article, we’re going to demonstrate how the landscape reading model can be represented using text networks and how this representation helps generate new ideas and insights in InfraNodus.

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  • Posted by | August 22, 2024

    Obsidian 3D Graph View Plugin with Network Science Insights

    A new graph view plugin for a popular note-taking app Obsidian that provides additional network theory insights to reveal the most influential ideas, clusters, and gaps between them.

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  • Posted by | April 9, 2023

    Personal Journal and Diary App with AI Text Analysis Features

    In this case study, we will demonstrate the advantages of keeping a personal journal and diary using an AI-based text analysis app. Advanced text analysis capacities combined with GPT AI functionality can dramatically improve the ability to self-reflect and enhance a regular introspection practice.

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  • Posted by | April 6, 2022

    Discover EU Grant Opportunities using Network Analysis

    In this case study, we will demonstrate how you can use text network analysis to analyze EU grant opportunities. We will demonstrate how you can use the graph to identify the most relevant topics in the existing grant proposals. We will also show how you can use network visualization to identify the structural gaps within.

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  • Posted by | November 30, 2020

    Variability of a Text, Ecology of Attention

    Modulating variability in a text or a conversation can have an interesting effect on its dynamics. A writer will never get stuck, a conversation will always be interesting, a discourse will stay ecological at its core. We propose an approach based on panarchy, embracing diversity and homogeneity at the same time, as applied to discursive practices.

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