NJournal Notes 2.0

https://en.wikipedia.org/wiki/Multifractal_system

A multifractal system is a generalization of a fractal system in which a single exponent (thefractal dimension) is not enough to describe its dynamics; instead, a continuous spectrum of exponents (the so-called singularity spectrum) is needed.^[1]

Multifractal systems are common in nature, especially geophysics. They include fully developed turbulence, stock market time series, real world scenes, the Sun’s magnetic field time series, heartbeat dynamics, human gait, and natural luminosity time series. Models have been proposed in various contexts ranging from turbulence in fluid dynamics to internet traffic, finance, image modeling, texture synthesis, meteorology, geophysics and more. The origin of multifractality in sequential (time series) data has been attributed to mathematical convergence effects related to the central limit theorem that have as foci of convergence the family of statistical distributions known as the Tweedie exponential dispersion models^[2]as well as the geometric Tweedie models.^[3] The first convergence effect yields monofractal sequences and the second convergence effect is responsible for variation in the fractal dimension of the monofractal sequences.^[4]

From a practical perspective, multifractal analysis uses the mathematical basis of multifractal theory to investigate datasets, often in conjunction with other methods offractal analysis and lacunarity analysis. The technique entails distorting datasets extracted from patterns to generate multifractal spectra that illustrate how scaling varies over the dataset. The techniques of multifractal analysis have been applied in a variety of practical situations such as predicting earthquakes and interpreting medical images.^[5][6][7]

Notes for the Nemetic Journal 1.0

From a Facebook Exchange...

Me: Fascinating. I'm trying to think through how that works for a vibrant conversation thread. It strikes me that your description is very similar to the design process which I describe as Notice.Engage. Mull. Exchange.


Her: Yes, "Notice.Engage. Mull. Exchange" seems apt, though takes on different dimensions when done in a studied way, allowing you to study and record the stages and parts for reference and connection later, trace and retrace steps looking for how they are embedded, and considering the various directions it can be taken. That's a great connection to make though, the high mental art of "noticing and engaging and mull over things to exchange what you learn" is what people who have really opened their minds do moment to moment. That it's an artful practice might be documented for teaching too, and always good to check one's self on.

Me: Our approach is to focus on the interactions instead of the content. For the content it is as you say it needs a journalist or a brilliant writer.

It works like this ( excuse the nemetic language ) 

A conversation is conducted by personas who emit nemes ( comments). In principle we can harvest the frequency of nemes. If you are lucky the nemes will contain the name of another persona. That is an indication of exchange. When the exchanges are persistent nStrings start to form. If there are two names in an exchange nStrings are beginning the process. Over time it will create a small nTube. As nTubes emerge they start to gain coherence. With persistence nTubes will reach a critical threshold. With the production of an artifact ( collaborative Exchange ) the whole conversation gains coherence by the emerging Intent to build something.

On a more practical level, if you have time/date stamped comments, you can map the frequencies of exchange. It will make it easier for the journalist to Notice what should be noticed. A click on the console would take anyone to the area of high frequency. Go through the content of the comments to produce a new neme ( the written piece ) which will produce a state change.

You can watch how this plays out at The Facebook Thread