A study of Twitter for understanding the concept of Everyday creativity

In earlier posts, I suggested that everyday creativity amounts to a thought translated into actions. The millions of tweets generated every day, gives us an excellent laboratory-setting to study everyday creativity.
Let’s set aside bots generating tweets for the moment, as they can be considered as a special case.

Everyday creativity as thoughts translated into actions supports the proposal that creativity is widely distributed.
How are the thoughts produced leading to a tweet being published produced?

Let’s start from my own experience. Every day I sign up to Twitter. I usually have had a thought I want to share. Why do I want to share it? because the idea has that property of novelty to me which I want others to know about.

Do I wonder if anyone else has thought about it in roughly the same way? Not really, although I might wonder how many other people receiving much the same stimuli will have much the same reaction.
The impulse to share is easily gratified through Twitter. Press send. Off it goes.
It is then given the mystic treatment known as the Twitter algorithm which decides who will read the tweet. This is the ghost in the machine, to use an old expression.
The next steps involve other Twitter users evaluating my idea. They have several options. They can ignore it, or like it (touch the heart shaped button). They can also resend it, with or without commenting on it.
These actions are through which the tweet gains attention (popularity, if you like). The process, like a radioactive decay process can accelerate, and go critical. Or, to use another metaphor we know recently from epidemiology, go viral.
The vast majority of tweets remain sub-critical, but a few increase in numbers of interactions exponentially, a meltdown which sometimes crashes the program.
There is no obvious way of detecting the viral process from the first tweet. That suggests it is a random process. But the selection process isn’t necessarily random. It may capture a more general reaction of the tweeters encountering it.
Put these two basic thoughts together and you have an idea generation and development on based on random variation and selective choice.
Sounds familiar? It’s the process of evolutionary change.
Yes, as research students will point out, I’ve bobbed about between the specific and the general.

For example, what about the bots I mentioned earlier? Certainly important. The embarrassing flip-flop of Elon Musk in the withdrawal of his bid for Twitter was said to be that the company’s value could not be calculated without more information about the number of bots and the number and nature of the tweets they generated.

At best I’m offering an explanatory line of thought.

In my next post, I look at a specific example of an everyday tweet and how its study helps understand more about the nature of everyday creativity. I’d welcome any comments, particularly thoughts turned into actions. You can even tweet them, if that’s your preference.