Twitter is full of false information. Even Twitter co-founder Ev Williams recognizes that there is a “junk information epidemic going on,” as “[ad-driven platforms] are benefiting from people generating attention at pretty much any cost.”
This video toolkit is intended to help you debunk dubious tweets. It was first developed in research by the Institute for Strategic Dialogue and the Arena Program at the London School of Economics to detect Russian social media influence during the German elections. It was also the basis for a related BuzzFeed article on a Russian bot farm and tweets about the AfD — the far-right party that will enter the German parliament for the first time.
But first: Where do these bots come from?
How Twitter bots are born
For an answer to that question I went into the dark web and returned with software that claims to build scores of Twitter bots in hours. I used this program just for a few minutes — for the sake of education.
The software creates hundreds of new email-addresses on the fly, with fake names and locations. It feeds each email address into Twitter’s signup page and spits out random usernames. If the name exists, another fake name is used. The software recognizes that Twitter wants additional checks, like a telephone number. I didn’t have to do a thing.
I stopped after just 2 minutes and had created my first 10 bots, which means the software may be capable of producing 300 bots per hour or 7,200 per day.
You can direct your brainless bot army to a certain country, city or continent by replying to tweets of real users. Or you can let them all shout out the same hashtags so you become the Twitter equivalent of the talk of the town: a trending topic.
Where is the money in all these fake accounts? Spam leads to ad revenue. And political tweets are bought by stakeholders, not merely through official ads but also through illegal bot farms.
During my virtual visit to a commercial hacking and bot farm, I was promised by staffer “Alexander” to get a top 10 position in trending topics in Germany during election day on the hashtag #AfD . The costs were relatively low: $180.
A Russian fake tweet specialist asks us how we wanted to have our army of bots: in C++?
Professional spammers and influencers prefer to write software for a bot army from scratch, in a programming language called C++, the hacker told me. Twitter has even more problems with detecting “handmade” bots. Buying the C++-enabled software was very expensive, more than $10,000.
How to fight the bots
Let’s fight back! With the proper tools it’s possible to find out more about any Twitter account. and track down dubious bots.
Tip 1: Find the exact minute of birth
Our target in this article will be Николай Кузнецов (Twitter handle @adjust_ps). If you read all 10 tips, you will understand why he is probably a Twitter bot, part of a bot farm that has a professional staff of 31 coders and six managers.
But first things first.
If you go to the profile page of any Twitter user and hover over the “Joined” date you can get the exact date and hour of creation. Now you know when someone started tweeting. Sometimes a bogus eyewitness account is born minutes after a breaking news event to lure people searching for the latest information towards spam content. So it’s good to know when the account started.
(Twitter Birthday does the same but doesn’t always respond. It also doesn’t respect your privacy, by showing your search to the rest of the world.)
Now we know when the account started, we want to know: with what?
Tip 2: Find the first words
Here’s why it makes sense to go back in time with a suspicious Twitter account: A bot will often begin its life shamelessly selling ideas or products right away.
You can find the first tweets through Advanced Twitter search, as shown in the video. Our guy just broadcasts links to YouTube videos in his first year and doesn’t interact with anybody. Link-spamming is the daily routine of bots.
If you don’t shy away from more nerdy approaches, you can also type in an equivalent formula directly in the Twitter search box. Type “from:” followed by the username, leave a space and then type “since:” and “until:” to insert your date range.
This formula can be typed straight into Twitter search.
Oddly enough, Twitter killed the service #firsttweet this year.
Let’s use tip 1 and tip 2 on another case. A Twitter account was very active during the final hours of the German vote. The user claimed irregularities during voting. People retweeted it.
Screenshot, (original tweet may be deleted)
The user claimed that AfD votes will be declared invalid. German authorities took it seriously. They officially replied to the user by saying that election fraud is not allowed and punishable.
Screenshot (original link)
Now here’s why you should go back to the exact time of birth of a Twitter account (tip 1) and find the first tweets (tip 2). When you do that, our (now suspended) user likes ….. to lick male genitalia without people noticing.
We think this tweet could be deleted, so we screenshot it.
With that, she loses (for most of us) credibility as being the best source for election fraud in Germany.
So it makes sense to have a first look at the first tweet to understand the context. A dumb bot wants you to buy Viagra or a political idea right away.
Tip 3: Check the followers
Analyzing the followers of a Twitter account can be revelatory based on your expectations of the account. If you follow a German account who wants to stop German Angela Merkel being leader of the country, logic dictates that most followers are from Germany (as shown in video).
But what do we expect from followers of our possible bot — a Russian guy who has posted a strange mix of ads, YouTube likes and support for German party #AfD?
Professionally created bots — not the “dumb” ones that rote-tweet spam links and have no name and no bio — tend to use profile pictures of real people, a bio and often a link to other social accounts.
To avoid spam detection, they choose their (automated) followers with care and spread them over all continents (as shown in the video). @Adjust_ps fits exactly that profile, so we’ll scrutinize him a little more in the next tip. Still, local users who tweet in their own language usually don’t have followers evenly spread over every continent, so if they do, it’s reason for you to research them a little further.
Tip 4: Find Twitter users in Facebook
Another pattern I’ve found with professional bots is that their Twitter account and email address are similar because their setup is automated. For other social media accounts, they will use an e-mail address based on the handle of their Twitter bot.
Let’s continue with our Russian account @adjust_ps.
Typing an email address directly into the search box of Facebook, searching and clicking on “People” will return the relevant user — if the user allows you to search by email. As the video shows, firstname.lastname@example.org is the correct address and leads directly to the Facebook account of our target. He uses the same photo on Facebook as on Twitter. (The owner disabled mail-checking in Facebook after we published this article).
So what do you think of his Facebook account? Almost every post is a link, with no personal comment attached. He is in thousands of commercial groups from all over the world, which is like bot behavior.
Our target likes to buy and sell
Tip 5. Find suspicious words in tweets
Tweetbeaver helps you find all kinds of details on a user’s Twitter activity and allows you to export it to Excel. One helpful feature is to get a summary of tweets with a certain keyword in it with the exact moment of posting. Our guy, adjust_ps had several tweets about AfD. Why?
Tip 6: Searching in big data
Using Graphika to study tweets from Russia about the German elections revealed two major hubs. One of them was our target.
Luca Hammer / FearlessDemocracy / Via fearlessdemocracy.org and Henk van Ess
The graph shows all kinds of tweets that promote AfD and probably are Russian. @Adjust_ps and @gyroscope999 are the opinion leaders.
Luca Hammer / FearlessDemocracy / Via fearlessdemocracy.org and Henk van Ess
In the second graph, we look at the similarities between the accounts. The larger circle and the smaller one, our target, are followed by many of the same sources. This is typical bot behaviour. In an army of bots, you follow each other.
When we asked the Russian bot farm directly if we could use @gyroscope999 and @adjust_ps for spreading political information, they claimed that they owned both.
Tip 7: Connect a made up Twitter handle to a real social media account
An anonymous Twitter user can become a real person with a full name on Facebook — via Foursquare.
People often use the same online nicknames in social media. Using this pattern allows us to find additional information. Replacing “twitter” with “foursquare” in a user’s profile url will get us a link to someone’s Facebook profile (and in this case, the full name).
Tip 8: Find a social score
It’s not perfect, but a social score helps you establish if a Twitter account is dead or alive. By inserting the Twitter handle (without the “@”) after klout.com/ you can find the social ranking of the user, which can help to decide whether the account is genuine or not.
Klout will give you some insight into what impact a user has on Twitter. You can earn 0 to 100 points. If your favorite source has a score of 0–10, be at least suspicious if they claim to be an expert.
If the score is 60 or higher, the source is well established in Twitter and gets a reasonable amounts of retweets. (Your Klout score may have an effect on how your Twitter help desk interactions play out.)
With a Klout score of 61, Bernd Luge, supporter of the AfD in Germany, seems not to be a bot. Professional bots try to hide their real reason of existence by being completely normal for months, hoping to get a high social score. Adjust_ps, for instance, doesn’t score like a normal bot, making him almost undetectable to Twitter.
Sooner or later, however, bots will spit random stuff, which you can check out via Klout too. Our target’s major concentrations include convertibles, copyright law, and flash drives — at the very least an eclectic mix.
Tip 9: How alive is the bot?
I always run Twitter accounts through Social Mention to get a faster insight on how (and whether) the user is communicating with other users. In our case, @Adjust_ps has only interacted with an Alexander (via a fake profile) — and yes, Alexander is one of the 31 staffers of our Russian bot farm.
Tip 10: When (and how) is your bot tweeting?
With Account Analysis you can get detailed insights into how the user tweets.
Our target tweets regularly and throughout the day. @Adjust_ps used a mobile phone only twice to tweet. The rest of time he used a web browser (“Twitter”) or shared YouTube videos.
Tweeting like this can be a sign of humanity — or a way well-programmed bots can avoid spam detection.
An earlier version of this story referred to the programming language “C+” when that should have been “C++”. We’re sorry sorry.