Generational Dynamics Forum - New Site

This would lead me to believe that what matters is an individual's view of their identity group and its survival being the important part to model. In that case then re-purposing what is known about the "radicalization" process of muslims would prove pretty useful if it could be extended to large gr...

https://hbr.org/2015/11/the-new-science-of-customer-emotions The process of quantifying and creating models around emotions seems like the territory of marketers and political analysts. If anyone knows one it may be helpful to try and re-purpose what is known into the context of GD than trying to r...

FishbellykanakaDude wrote: Yaʻ know,.. itʻs getting to be REALLY hard to be a simple person, such as myself, around here these days! Iʻm feelinʻ the pressure, people,.. Iʻm really feelinʻ it!!

..all this talk about cake, and Camus, and whether eating or having comes first,.. SHEESH!

Aye Aye Cap'n fish guts dude!

Singular value composition (SVD) can also be useful with dimensionality reduction https://www.youtube.com/watch?v=P5mlg91as1c . Also important to remember images are a combination of many dimensions i.e. images are composed of a Red Green Blue spectrum (or HSV, etc.) and these are combined to give t...

If the driver is typically the younger generations that get the short end of the stick in may be helpful to limit the analysis to these groups. At the least try to narrow it to the groups that get effected the most. The corruption and negative consequences will probably vary culture to culture but a...

Any kind of function combining a variety of different variables (especially with PCA) should have the values normalized between some values ([0,1]) to make sure the wider range of values specific variables can take on don't lead to "assigning more credit" to the variables contribution as PCA provide...

If any visualization is possible it would need to reduce all the variables into one output via some function because you would need 2 dimensions for the spatial representation of earth. There are plenty of techniques for dimensionality reduction. PCA is the tried and true if you don't care about bei...

For clarity too, I don't know if I would refer to timing as high frequency and inevitability as low frequency. This may be my ignorance but, from my perspective by just watching the video repeatedly, it is that when our signal ("energy metric") is looked at in narrow time spans there is a wide range...

Ideally they might have specific equations that could precisely say how the accuracy of the model increases as we look at larger and larger periods of time and how well/far it extends into the future. It seems like this would probably be approximately what we would want. Obviously this would have to...

I'm sure the low frequency "inevitability" side of the picture is well understood and not as important. Additionally, the farther one looks back in time the less data one would have. If we are trying to filter out noise in the high frequency side of the picture it may be beneficial to talk to a high...