I think the hypothesis on Freddie’s is that activity would decrease when something interesting is about to happen, because employees wouldn’t have any leisure time.
I think stripping Google Maps activity data would probably make for a better dataset, since, as OP points out, this is largely just a graph of the Twitter account’s posting history. I think that such a dataset would have to be collected over time, by scraping Maps every few hours or so, unless Google surfaces past activity data through some API endpoint or another.
The big advantage of scraping the twitter account’s posting history is that it lets you back test. Any clever analysis we do now could only be forward tested, even if google surfaced the relevant data.
I don’t think this is right, but maybe I will calculate new indices to account for this. For one thing, I think the idea is that Pentagon employees are less likely to frequent gay bars than other DC residents. For another, there exist tweets in the dataset that look like this:
HIGH activity is being reported at the closest Papa Johns to the Pentagon.
Freddies Beach Bar is reporting abnormally low activity levels for a Saturday at 7:11pm ET.
Classic indicator for potential overtime at the Pentagon.
I think the hypothesis on Freddie’s is that activity would decrease when something interesting is about to happen, because employees wouldn’t have any leisure time.
I think stripping Google Maps activity data would probably make for a better dataset, since, as OP points out, this is largely just a graph of the Twitter account’s posting history. I think that such a dataset would have to be collected over time, by scraping Maps every few hours or so, unless Google surfaces past activity data through some API endpoint or another.
The big advantage of scraping the twitter account’s posting history is that it lets you back test. Any clever analysis we do now could only be forward tested, even if google surfaced the relevant data.
This!
I don’t think this is right, but maybe I will calculate new indices to account for this. For one thing, I think the idea is that Pentagon employees are less likely to frequent gay bars than other DC residents. For another, there exist tweets in the dataset that look like this: