I started aggregating and analyzing network data from CT (Crypto Twitter)(influencers, projects, developers).
Here is what I've learned:
1. Tracking who follows is very noisy.
It might be an interesting flex on popularity (Remember Klout?), but it does not seem to lead to actionable insights. At scale, you can't really control who follows you.
2. Tracking who your targets follow is VERY interesting
This provides an entirely new level of discovery that has not been available to me before. This is a level of curation that the Twitter algorithms seem to miss. I've found quite a new new accounts with less than 500 followers whose content is VERY good.
3. Pseudonymous crypto people abandon old accounts and create new ones
With some simple network analysis I'm able to re-discover them again (it seems). If I continually monitor the a curated list of crypto twitter accounts, I believe it is possible to continually discover new and interesting rabbit holes.
4. Twitter is a great source for primary data in the crypto space
There is a lot of data that only lives on twitter, and it comes out 280 characters at a time. People are now blogging on the platform in the shape of "threads" (multiple tweets sent out in serial fashion.
Some of these tweets contain information sadly get lost in the doom scrolling and ever-continuous feed. I foresee a time very soon when I might want to add some archiving and NLP to some of these accounts that I'm tracking.