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  • Visualization of Text’s Polysingularity Using Network Analysis

    Figure 10: Most prominent communities in both texts.

    In this research we propose a method for visualizing text’s polysingularity: the multiple clusters of meaning circulation contained within a text. These clusters can be described as “strange attractors” (to use the term from dynamical systems theory), which are actualized during the process of reading. We use network analysis in order to plot the text’s structure onto a two-dimensional plane and represent these strange attractors as the communities of co-occurring nodes, positioned within the graph depending on their influence for the production of meaning.

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  • Competitive Intelligence and Market Research with GPT-3 AI and Networks

    AI to better understand your competition and customers. You can apply this methodology to your own data using the InfraNodus Marketing Research app.

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  • Network Thinking and Mindmapping for Ideation and Brainstorming

    How to enhance your group ideation and brainstorming workflows using network analysis and mindmapping. Learn how to synthesize important ideas without losing the nuance.

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  • 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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  • Brainstorming Techniques for Writing using Text Networks

    Most brainstorming techniques have one thing in common: they are about connecting ideas. The next step is to put those ideas to writing. In this article, we will demonstrate a new approach to brainstorming using text network analysis. We will be using the InfraNodus brainstorming tool, which converts plain text into a mind map and then proposes the new connections between them.

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