Situational awareness (digital, near real time?)
This is equal parts suggestion, question, and brainstorming – I’m looking for ideas for gathering [near real time] situational awareness.
As I’ve read this site and others I get the impression that different parts of the country are experiencing things in very different ways. I see people sharing images of empty shelves in a store on the other side of the country but down the street things seem “normal.” I realize a lot of online content is more anecdote and less data but I also figure that with a lot of anecdotes you might be able to tease out some data/trends.
One idea (not my favorite) is twitter, there are some interesting advanced searches.
For instance if I want to see tweets within 50 miles of Washington DC, this search term seems to work:
likewise if I want to search for recent tweets about “groceries” or “grocery store” this seems to work (and would perhaps work through the end of the year?) this search string appears to work:
(groceries OR grocery store) until:2020-12-31 since:2020-11-15 -filter:replies
It seems I can combine these manually, too:
(groceries OR grocery store) until:2020-12-31 since:2020-11-15 -filter:replies near:”38.901862736383556,-77.0102291245727″ within:50.07mi
I feel like with a few saved search strings you could search your area for recent activity at various distances. You still have to sift through random people on twitter but maybe there are more filters/tips I’m not aware of that others could share.
My only other thoughts on “real time awareness” are things like crime maps, however these often lack context (trends over time, comparisons, etc) so its hard to know what a “normal” amount of crime looks like. These also tend to be specific to certain areas and each area may have different reporting parameters making it hard to gauge changes between jurisdictions.
Not sure how many tech/code savvy people are on here, but this was inspired by a surge in ‘bots’ to scrape retail websites for available stock of PC video cards. I thought it would be neat to scrape data from retailers by store for stock of things like toilet paper or other “in demand” items to get a sense of where demand was spiking, but thats probably a bit niche and beyond my coding skills.
Any other ideas, either different resources or tips for refining twitter searches?