InfraNodus Research Framework and Methodology
InfraNodus proposes a framework for research, which is based on ecological thinking where it considers any discourse as a dynamic ecosystem of interdependent parts. The objective is to bring those parts into play by inducing variability across two spectrums: scale and intent.
A researcher using InfraNodus framework will be encouraged to become aware both of high-level ideas (big scale) and underlying nuances (small scale). They will also be encouraged to alternate between connecting ideas (focused intent) as well as deconstructing the discourse and looking for new ideas beyond its immediate limits (exploratory intent).
Such approach ensures that a research process remains coherent and, yet, open to external influence. It is inspired by dynamical systems theory, network science, and deconstrutivism. It helps discover patterns, relations, interesting perspectives, new insights, blind spots, and knowledge gaps rather than fixed ideas and conclusive findings.
1. Scale and Intent Variability
One of the main tenets of stable ecological systems are diversity and adaptability. These qualities make them robust and open to change. InfraNodus represents a discourse as a network of ideas and then encourages the user to explore it in a way that opens up multiple diverse perspectives.
This is done through instilling cognitive variability across mainly two spectrums: scale and intent.
The first spectrum, that of the scale (vertical Y axis), is encouraging the user to shift between different scales: from small scale (zooming in onto specific concepts) to big scale (zooming out to see the whole picture and topical patterns).
The second spectrum, that of intent (horizontal X axis), is encouraging the user to shift between different types of intent: from exploration (exploring periphery and deconstructing ideas) to focus (bridging the gaps, connecting ideas).
This kind of approach has several advantages that makes a research process, perception, and reading more diverse and adaptable.
2. Advantage: Open-Minded Coherency
First, constant shifting across different scale makes sure that the discourse or our reading of it stays coherent, but not too biased or too dispersed. The ideas are organised into topical clusters that are distinct from one another (diversity) yet, connect on the global scale (coherency).
Second, constant shifting between exploration and focus ensures that there is a constant influx of new ideas into the discourse (exploration) and, at the same time, those ideas also get connected into conceptual clusters that make sense. This ensures that we stay open to new ideas but without losing the track of the key concepts.
Obviously, this does not mean that a discourse has an "ideal" state. We approach cognitive variability as a dynamic process that is also context-specific. That is why distinguish 4 different states for each discourse, which has a different combinations of the scale / intent parameters.
A discourse is always a part of an ecosystem. There are some environments and situations that require discourses to be biased and some other contexts that require for discourses to be highly dispersed.
3. Implementation
In InfraNodus, the research framework outlined above is promoted through modulating cognitive variability using the interface elements, workflow scenarios, and interface items that encourage the user to switch attention, intention, and scale.
We propose four different workflows through our interface that can be used to:
- 1. Enhance Understanding of a Discourse
- 2. Get an Overview of an Idea
- 3. Refresh One's Memory of a Text
- 4. Develop a Discourse from an Idea
An example of one such workflow as implemented in InfraNodus is shown below:
Each of the workflows proposes several actions that alternate between scales (zooming in and zooming out) as well as the intent (exploration vs. focus, deconstruction vs. construction).
Our internal studies (link) have shown that such approach leads to a more comprehensive understanding of a topic or text as the reader is encouraged to switch between different perspectives and to look at the ideas presented from multiple viewpoints, thus, enriching their understanding of context and avoiding their built-in bias.
A research framework based on induced cognitive variability helps us escape echo chambers and avoid totalitarian thinking, because it promotes diversity and openness as a dynamic practice in writing and reading.
4. Bias and Poetry
By default, our framework helps to induce an optimal level of coherency. However, this approach can also be used to shift towards higher bias or, on the contrary, towards a high level of dispersion and even incoherency. There are several reasons why this may be useful and interesting.
For instance, when a discourse needs to mobilise people for a collective action it will work better if it is biased. At the same time, a highly biased discourse may also be highly ideological and may have negative effect in the long-term, especially in the contexts that have totalitarian tendencies (e.g. informational trends, media-fuelled frenzy, uniform opinions formed around fear-based narratives).
On the other side, if we talk about poetry, it may be beneficial for it to be highly dispersed as it will leave multiple structural gaps in the meaning, which the reader has the pleasure to fill with their own thoughts and emotions.
In general, however, most situations will benefit from a discourse that combines multiple properties over a period of time: operating at multiple scales (granular concepts that align into big themes) and encouraging multiple intents (from exploration to focus).
5. More Information
To read more about this approach, please, see our research article on Ecological Thinking Framework on Nodus Labs and also the article on Cognitve Variability of Thinking on our Support Portal.
The basic workflow outline is available on our support portal and directly in InfraNodus' interface
Try It Yourself
To try cognitive variability on your own ideas or texts, please, sign up for an account or log in if you already have one:
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