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Peak data mysticism and almanac goodness: astrology Excel sheets which fill themselves on DOB input

A few hand-picked company names from the Panama Papers database

Before it completely dies in darkness, here is a proper ending to this log-thread.

The project is now online at:
and the code:

This will keep growing for the foreseeable future 😉

- - - - - - [ END OF THREAD ] - - - - - -

Presenting Counting the Future at the RCA today: IED students this morning, and to my fellow researchers this afternoon. Good opportunity to try and pull things together, and to name things:

☄️✏️⚡️ epic meta-diagramming ⚡️🌊💻

The citation link between Fisher's linear separation of the Iris dataset (Annals of Eugenics, 1936)—widely used as a demo and/or benchmark for classifiers—and Support-Vector Machines from Cortes and Vapnik (1995).

more on SVMs in Mackenzie's Machines Learners (ch.6 Patterns and Differences)


Cortes and Vapnik:

On the development front, made some progress this week. The graph view is taking shape (although plenty of 'special cases' to hard code which is part of the fun), and image view + reference view were nice and easy to implement.

the back end is getting ... rhizomatic

Extending the 'Social Physics' thread from earlier to its current incarnation. First as Alex Pentland's Human Dynamics Lab at MIT, then with the inevitable spinoff startup, complete with a crypto-currency (and upcoming ICO) for "unlimited accurate predictions".


Carr's critical review:


Revisited a key paper today, 'Big Data, social physics, and spatial analysis: The early years', Barnes & Wilson, 2014.

Mapping out the trajectory from Quetelet to GIS at Harvard put the editor to the test. It works! much easier than anything I was able to do with CSVs, and more flexible. Not sure this if this is truly rhizomatic as Corner or Deleuze would have it, but it definitely feels like 'burrowing'.

Prior art: Histograph is a digital humanities project mapping relationships between historical figures based on co-occurrences of names in documents. It also uses a database, although in the 'network changing over time' way, where I have gone with a 'the network is the timeline' approach.

👍 Wired: history, graph database, european integration.
👎 Tired: big data, very hard to use, comical computational mistakes.

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