On his profile page, @leedelon lists London as his home. His tweet timings in GMT look reasonable. So far, so good. . .
It gets slightly more complicated when you look at @leedelon's schedule alongside the tweets indicating his country of residence. His schedule remains fairly consistent throughout, which is inconsistent with the 8 hour time difference between Japan and UK in the summer.
For most of us, the year of our birth tends to be relatively constant, and we tend to get one year older every year. As you can see, things aren't nearly so simple for @leedelon.
As a London (maybe) resident, we might expect @leedelon to use UK spellings of words that are spelled differently in the UK and US. This does not turn out to be the case.
What does @leedelon tweet about? This chart shows the percentage of his tweets containing keywords related to various themes; overall, 58% of @leedelon's tweets contain one or more of these terms.
Here are some examples of @leedelon's tweets corresponding to Kremlin agitprop themes: Crimea=Russia and Putin=awesome (and invited to nuke the West).
For a bricklayer in the UK, @leedelon seems to be far more interested in US than UK politics. Apparently it has something to do with spole.
Meet @ShawneeDeaver. This account's first tweet - and only non-reply tweet - is 2scEY0T, an apparently random 7-character alphanumeric code. The rest of the tweets are replies sent within hours of its creation; the collage is representative. (Thanks @OlgaNYC1211 for the lead).
We decided to look for more accounts like it. We started by harvesting the recent replies to the accounts that @ShawneeDeaver replied to, and filtering the results to accounts with a 7-character code as their first tweet and all subsequent tweets being quickly-launched replies.
Let's take an updated look at the traffic related to Russia Insider, a Russian news site featuring sections such as "Western Collapse", "The Jewish Question", "Free Assange", "Russiahoax", and "EU Conservative Uprising".
(previous Russia Insider thread in which failed Congressional Candidate Paul Nehlen featured prominently)
While looking for streams of the Kavanaugh confirmation cloture vote yesterday, we stumbled on @Seekandfind, an account that linked Russia Today's stream. Spoiler alert - this account is (at least presently) a bot with signs of some human interjections.
This account is extremely high-volume (900+ tweets per day at present) and uses a massive cornucopia of different automation tools to tweet (mostly Microsoft PowerApps, Buffer, Integromat, IFTTT, and Zapier).
What does @Seekandfind tweet about? 37.1% of tweets contain one or more of the keywords shown in this chart - the Trump, Hillary Clinton, MSM/fake news, and deep state categories being the most prominent.
On October 2nd, the news came out that envelopes containing suspected ricin had been mailed to the Pentagon and the White House. We downloaded tweets containing the word "ricin" a few hours after the news broke, resulting in 45007 tweets from 29308 accounts.
Here's the retweet network for "ricin" on 2018-10-02. It consists almost entirely of right wing accounts, most of which are speculating that the ricin mailing was left-wing terrorism.
We tested a sample of 10000 of the accounts with ricin tweets for automation (based on either 24/7 activity or 90%+ of tweets being posted via automation services/custom apps). 817 (8.2%) were flagged as bots. Let's look at a few of them.
Yesterday (2018-10-02), four members of the white supremacist group known as the "Rise Above Movement" were arrested by the feds for their part in the violence at the #UniteTheRight rally in Charlottesville in August 2018. Let's take a look at related Twitter traffic.
(previous thread on the Twitter activity surrounding the #UniteTheRight hashtag leading up to and during the rally last year.)
We downloaded tweets containing "Charlottesville" and "arrests", resulting in 15082 tweets from 12331 accounts beginning with the first report of the arrests (from @HenryGraff).
How does one go about detecting Twitter bots (automated accounts)? Let's take a look at three different tests for detecting signs of automation, and try them on three different sample sets of accounts.
The first two tests may be familiar from previous threads:
1. 24/7 tweet activity - this could point to multiple human operators, but is usually the result of automation/tweet scheduling. 2. Use of automation services such as IFTTT or custom apps built with the Twitter API.
The tweet schedule plots shown in the previous tweet can be used to visually perform both these tests. You can generate them yourself for accounts of interest here: makeadverbsgreatagain.org/allegedly