Dear Twitter: Please Learn about CUP’A and Check Out My Publications

Dear Twitter,

As you may have noticed, I don’t visit you very often. If you want to attract me, try serving me content that is not only superficially Appealing to me (by this, I am referring to the “A” in “CUP’A“), but that is actually of high Caliber, Usefulness and Potency (yes, that is the part you are meant to drink from, the “CUP”). In other words, please become a content discovery tool towards which I would turn with cognitive enthusiasm.

To know me well, Twitter, is to know that CUP’A is defined in Cognitive Productivity: Using Knowledge to Become Profoundly Effective and in Cognitive Productivity with macOS®: 7 Principles for Getting Smarter with Knowledge.

Once you’ve gotten the hang of those concepts, Twitter, then please get to know me better. Index and interpret what I like to write about. Check out my academic publications. But do a lot better job than (not very hard to beat) and Research Gate in learning what is relevant to me. Look at the articles I cite. Try to figure out what I will be citing next.

As you should know

However, I would find it rather creepy if you know that later this year, I will also blog at CogSci Apps, which we are about to revamp. But having previously tipped my hand, I hope you know that we are about to release a new macOS app to boost our users’ cognitive productivity.

Given that I have gone to the trouble of indicating what my projects are, as well as my current and future books, perhaps you can consider them in building your profile of me. (My books and papers are available in PDF, which you can index.) In the future, I hope that when I add content to these pages, you will automatically update your model of me. I imagine other researchers would like you to understand them too without them needing to write letters to you on their blogs. (The whole point is that we’re very busy, you know.)

I’m sure that it would be helpful for me to classify my publications using JSON-LD schemas. Perhaps you can help me by suggesting some JSON-LD schemas I should use for you to better understand what I write about. (Maybe my readers will suggest some, and a helpful WordPress plugin for JSON-LD.)

By understanding what scientists, bloggers and authors write about, you’ll get a much better understanding of what they want to read. This will give you a clue not only about what topics are relevant to us, but also the standards we value, i.e., “CUP” (caliber, utility, and potency), rather than “A” (appeal).

In other words, I’d like you to serve me tweets about recent highly relevant books, scientific articles, and blog posts that will shape my thinking, future writing and work.

In my Cognitive Productivity books, you will also find some useful references on a subject that you should become more expert, namely discovery. They are in various chapters, but in particular consider the “Surf” and “Manage” chapters. You will, for example, find references to a pertinent book by Paul Thagard.

Thagard, P. (2012). The cognitive science of science: Explanation, discovery, and conceptual change. Cambridge, MA: MIT Press.

But many other scientists, referenced in my books, have written on the subject. Being Canadian, in this context it’s hard for me not to mention a great Canuck who, perhaps, should have gotten a Nobel prize for his work on stress:

Selye, H. (1964). From dream to discovery: On being a scientist. New York, NY: McGraw Hill.

It’s particularly sad that Hans Selye didn’t get that prize, given that his motto was, “Earn thy neighbor’s love”. But he knew that for writers his motto implied, “Earn thy reader’s reading time and respect”, which he did. Lest you infer that I am prone to digressing: of you, Twitter, I request “Earn researchers’ time”.

I assume you can also accumulate some very valuable patents by cracking the AI problems implicit in this post. Presumably, you and your competitors are already working on such projects. You will earn my time when you make more progress on them.

In any event, I’m hopeful (if not confident) that, based on the highly discriminative tags I’ve applied to this post, you will very soon discover, read and attempt to implement the suggestions it contains. You might later look back at CUP’A and find that it, itself, was high on CUP’A, but that it is no longer potent for you (because you’ll already have been transformed by it.)

And for that, dear Twitter, other researchers and I will thank you.

Published by

Luc P. Beaudoin

Head of CogZest. Author of Cognitive Productivity books. Co-founder of CogSci Apps Corp. Adjunct Professor of Education, Simon Fraser University. Why, Where, and What I Write. See About Me for more information.

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