Key Findings

The operation was carefully planned, with accounts often registered months before they were used – and well in advance of the 2016 U.S. presidential election. The average time between account creation and first tweet was 177 days.

A core group of main accounts was used to push out new content. These were often ”fake news” outlets masquerading as regional news outlets or pretended to be political organizations.

A much larger pool of auxiliary accounts was used to amplify messages pushed out by the main accounts. These usually pretended to be individuals.

The campaign directed propaganda at both sides of the liberal/conservative political divide in the U.S., in particular the more disaffected elements of both camps.

Most accounts were primarily automated, but they would frequently show signs of manual intervention, such as posting original content or slightly changing the wording of reposted contented, presumably in an attempt to make them appear more authentic and reduce the risk of their deletion. Fake news accounts were set up to monitor blog activity and automatically push new blog posts to Twitter. Auxiliary accounts were configured to retweet content pushed out by the main accounts.

The most retweeted account garnered over 6 million retweets. Only a small fraction (1,850) of those retweets came from other accounts within the dataset, meaning many of the retweets could have come from genuine Twitter users.

One of the main talking points of the 2016 U.S. presidential election campaign involved attempts to surreptitiously influence public opinion using social media campaigns. In the months after the election, it quickly became apparent that a sophisticated propaganda operation had been directed against American voters.

Not surprisingly, news of these campaigns caused widespread public concern, prompting social media firms to launch investigations into whether their services had been misused. In October 2018, Twitter released a massive dataset of content posted on its service by the Internet Research Agency (IRA), a Russian company responsible for the largest propaganda campaign directed against the U.S.

The dataset consisted of 3,836 Twitter accounts and nearly 10 million tweets. These accounts had amassed almost 6.4 million followers and were following 3.2 million accounts. The sheer volume of data was enormous, more than 275 GB.

The archive has proven to be a treasure trove of information on how the IRA’s propaganda campaign operated. For example, prior to the release, many people assumed that its posts were focused on just one side of the political spectrum. Once the data was made public, it quickly became obvious that in order to achieve its goal, the campaign directed propaganda at both sides of the liberal/conservative political divide in the U.S., in particular the more disaffected elements of both camps. The main objective of the campaign instead appeared to be sowing discord by attempting to inflame opinions on both sides. This was not just confined to the online sphere. Several of the accounts were used to organize political rallies in the U.S. and some of the most influential accounts in the dataset were used to promote these events to the largest possible audience.

However, believing that there is a lot to learn from this data beyond its messages and target audience, we decided to carry out some in-depth analysis of the archive to learn more about how this propaganda campaign worked. What we discovered was that this was not an ad-hoc response to political events in the U.S. Instead, the evidence points to a carefully planned and coordinated operation, with the groundwork often laid months in advance.

While the tactics employed changed somewhat over time, the basic template for this operation remained the same, utilizing a small core of accounts to push out new content and a wider pool of automated accounts to amplify those messages.

Along the way, we also came across some interesting bits of information, such as what appeared to be some rogue operators using monetized link-shortening services to make some money on the side.

Different account types

Once we started analyzing the data, it became apparent that the accounts could be divided into two main categories, which we called main accounts and auxiliary accounts. Each category had different characteristics and played a different role.

Main accounts had at least 10,000 followers but followed substantially fewer accounts. They were primarily used to publish new tweets.

Auxiliary accounts had less than 10,000 followers, but often followed more accounts than that. Their main purpose was to retweet messages from other accounts, although they were also used to publish original tweets. Not surprisingly, the majority of accounts were auxiliary accounts. We identified 123 main accounts and 3,713 auxiliary accounts within the dataset.

Main accounts generally were ”fake news” outlets masquerading as regional news outlets, or pretending to be political parties or hashtag games—the popular Twitter game that involves people sharing anecdotes or jokes based on a single theme, such as #5WordsToRuinADate. Based on their creation date they were usually created individually or in small batches. The default language selected for main accounts was always either English or Russian.

Auxiliary accounts usually pretended to be individuals, spreading the content created by the main accounts by retweeting it. These accounts were usually created in batches and sometimes hundreds of auxiliary accounts were created on the same day. For example, during May 2014, seven fake news accounts were set up by the agency, along with 514 auxiliary accounts.

Many of the accounts were created long before they were used. The average time between account creation and first tweet was 177 days. The average length of time an account remained active was 429 days.