Felipe Hoffa, a Google developer advocate, uses BigQuery to analyze large public datasets like GitHub, Hacker News, and Reddit.
HN commenters cite his tabs-versus-spaces analysis of GitHub files and his Hacker News and Reddit datasets on BigQuery; he also appears answering questions on dataset updates.
I believe the number of voters in key districts needed to swing the electoral college to Clinton was in the tens of thousands. If it was targeted perfectly (which of course is impossible), that's almost two dollars a person that needed to be influenced. How many Facebook ads impressions does that buy per person? While I think it's unlikely that anyone could have accurately targeted to that degree, it does put into perspective just how important targeted advertising might be to something like this.
Additionally (and I think more likely), the advertising might have been been used more as an agitation device, and to reduce the trust in traditional information through highly effective misinformation. If you can start viral memes, it doesn't matter how many impressions you paid for, what's important is how far the meme spreads in the end. A single shared article can lead to tens of millions of views and re-shares. In this case, money is purely a way to help get critical mass for your specially crafted meme, so it doesn't necessarily compare to candidate spending directly, which needs to both educate and counteract opponent messaging. Targeted disinformation can just ignore failed meme campaigns and counteractions to them and move onto the next meme, since it's effectively anonymous.
1: https://medium.com/@hoffa/hillary-only-needed-to-switch-53-650-voters-to-win-94940ff263b7
I recently wrote a little Python script to scrape the url from top submissions to Reddit's /r/The_Donald vs. /r/EnoughTrumpSpam to get an idea of the most conservative-leaning and liberal-leaning news outlets (e.g. more specifically which news sites conservative-leaning and liberal-leaning redditors use to support their respective narratives). Here are the results:
https://i.redd.it/45ezt3j9hziy.png
Edit: Oh and I almost forgot (and to bring this full circle) a Googler saw my post about this and made an interactive version:
https://medium.com/@hoffa/reddit-favorite-sources-the-most-linked-sites-expanded-and-interactive-79070d648573
Edit: and to really bring this full circle, this Googler made an interactive version about HN:
https://medium.com/@hoffa/hacker-news-on-bigquery-now-with-daily-updates-so-what-are-the-top-domains-963d3c68b2e2
The GitHub Archive dataset was updated as well. Example BigQuery to get the Top Repositories from 2015-2016 YTD, by the number of Stars given during that time:
SELECT repo.id, repo.name, COUNT(*) as num_stars
FROM TABLE_DATE_RANGE([githubarchive:day.], TIMESTAMP('2015-01-01'), TIMESTAMP('2016-12-31'))
WHERE type = "WatchEvent"
GROUP BY repo.id, repo.name
ORDER BY num_stars DESC
LIMIT 1000
Which results in this output: https://docs.google.com/spreadsheets/d/16yDS2wDdDOTxjVsjGvWmpHVsOIU65wLEjXFHDtDeKU4/edit?usp=sharing
Since the query only hits 3 columns, it only uses 15.4GB of data (out of a 1TB allowance)
More information on the GitHub Archive changes: https://medium.com/@hoffa/github-archive-fully-updated-notice-some-breaking-changes-64e7e7cd0967
Wouldn't this make sense?
https://medium.com/@hoffa/400-000-github-repositories-1-billion-files-14-terabytes-of-code-spaces-or-tabs-7cfe0b5dd7fd#.j6ki2b7og
So the number of people that prefer spaces far outweighs the tabbers.
Now, take the pool of people that use spaces and tabs and let them compete for a 100k job. 9 times out of 10 even if randomly hired it will be a space person.
Also, as a by the way, on the medium post. The reason Java has so much tabs is specifically due to the default Eclipse formatting that prefers a mix Tab/Space approach. Which is absolutely horrifying in my personal opinion. I don't have any numbers but Eclipse probably holds 80%, followed by Netbeans and/or IntelliJ. (both of which default to spaces)
Hi, Felipe Hoffa at Google here.
We're aware the dataset hasn't been updated since a month ago, and we are working to fix it. You can track the issue here:
- https://issuetracker.google.com/issues/127132286
In the meantime you can still play with the dataset, and dig into the full history of Hacker News - less this last month. I left some interesting queries to get you started here:
- https://medium.com/@hoffa/hacker-news-on-bigquery-now-with-daily-updates-so-what-are-the-top-domains-963d3c68b2e2
By popular vote: spaces. See https://medium.com/@hoffa/400-000-github-repositories-1-billion-files-14-terabytes-of-code-spaces-or-tabs-7cfe0b5dd7fd. Previous discussion: https://news.ycombinator.com/item?id=12397246