Here's some of the sources I've seen when working on that topic [1] : Census data, Phone books, Academic bibliographic databases (web of science, pubmed), list of athletes at olympic games, Wikipedia, LinkedIn, ...
Oh yeah ! Onomastics (the study of names) is very cool ! And a nice data point to add to personalized data. I did a project with that a while ago to study discrimination in France (https://namograph.antonomase.fr/) and it worked pretty well as long as you have large samples and stick to distributions comparisons.
Location: Berlin, Germany.
Remote: Yes
Willing to relocate: Why not
Technologies: People, Python
Résumé/CV: https://www.antonomase.fr/
Email: antoine dot mazieres at gmail dot com
Neuroscience inspired machine learning is what's happening now. Others approaches are logic-based and evolutionnary inspirations. A nice piece commenting on some of that: https://neurovenge.antonomase.fr/
Hi, I didn't release the code of the crawler, first, because it was not well-crafted enough to be released (quick and dirty linear programming), and second, because any change in the site you crawl calls for recrafting your code.
I used python, sometimes with Beautifulsoup, sometimes with lxml, both are very good for crawling. I would say BS is easier, and LXML cleaner.