We initially visualized the full network of users that Russian bots mentioned using a directed graph. In the photo, we see trolls in red and real users in green. While the graph displays around 14,000 accounts, approximately 200 of these are troll accounts— indicating a large impact on real accounts per troll. Next, we took a closer look at the accounts that were mentioned most frequently.
Here, we see accounts that were mentioned by Russian trolls at least ten times. Notice that we now start to see a clearer pattern; there are clusters of topics and users that each troll or group of trolls targeted, indicating that these mentions were strategic and not random.
In the three main groups of mentions shown, we see differences in the content of mentions from trolls to real users as well as the identity of the real users. We labeled each of the three groups with the most common content category of the tweets.
Group 1 was the least dense of all groups with a total of about 400 tweets and only 9 real accounts. We found that the majority of the real users in this group tweeted left-leaning content, and only one user supported Trump. Interestingly, the tweets from these trolls were not pushing a certain agenda; instead, trolls were retweeting whatever the real accounts had posted. For instance, @toneporter, a fake account, mentioned the left-leaning real account @chiefplan1 by tweeting “RT @chiefplan1: Debate watch: Notice how, w/every lie Delusional Donnie tells, bags under his eyes get bigger--fuller of baggage...” On the other hand, other troll accounts retweeted a real pro-Trump account saying “RT @Shane_Rodenbeck: #IHaveARightToKnow if Obama is planning on moving back to his birthplace, Kenya.” Therefore, in contrast to possible expectations that Russian trolls would primarily retweet pro-Trump content, this group of trolls primarily retweeted anti-Trump content— indicating a more complex strategy to polarize American dialogue online.
When looking at the most common words within the tweets of this group, “Hillary” comes up first at 77 separate occurrences, and Trump second with 70 occurrences. The numbers drop sharply for all other words, though we see a focus on the presidential debates through words such as delusional (36 occurrences), vote (32 occurrences), healthcare (26 occurrences), and RejectedDebateTopics (14 occurrences).
Next, group 2 was considerably more dense than group 1, consisting of about 1300 tweets and 25 real accounts. Similar to group 1, most of the real accounts here were liberal, but they were much more well-known public figures— with a particularly high number of activists. For instance, we see @shaunking, @jamilsmith, @revjjackson and @deray, all of whom are African American activists with followers between 150k to +1m. The trolls in this group occasionally exhibited opinions different from the real account they mentioned, and, at times, used mentions to attack the real account’s statements. For instance, @ten_gop tweeted “WOW! @Deray and @POTUS[referring to Obama] plotting against America for nearly 4.5 hours! So how many plans for riots?!” This exemplifies one of group 2’s trolling strategies in using mentions to magnify their voice by responding to real public figures.
The general topics that were discussed in group 2 focused on news headlines speculating Trump’s policies. For example, @javonhidp, a fake account, tweeted “RT @blicqer: ▶ On Trump’s Education Policy https://t.co/AgECMmglkY @NatCounterPunch” Whether the tweets were supportive of the mentioned headline or not, we noticed significant visibility for Donald Trump in this group and fewer mentions of Hillary Clinton. The word “Trump” showed up 441 times and “Donald” 154 times, while “Clinton” showed up only 117 times and “Hillary” 69 times. These numbers show that these trolls gave Trump more visibility than Clinton.
Lastly, group 3 was the most dense with about 5000 tweets and 60 real accounts. This group of trolls mentioned the real accounts of prominent Trump supporters and public figures from the GOP. We see @tedcruz, @seanhannity, @erictrump and @mike_pence. Unlike groups 1 and 2, group 3 had fewer trolls than real accounts.
In this group, Trump and Clinton were mentioned a similar number of times at 946 and 845 occurrences respectively. When we look at the content of the tweets, they were mostly retweets of strong attacks on Hillary Clinton or vigorous endorsements of Trump. Some of the common attacks against Hillary Clinton referred to Clinton’s emails and Benghazi, and hashtags such as #NeverHillary was among the most used. One of the most frequently retweeted tweets was “RT @DonaldJTrumpJr: Bernie Delegate: DNC is Replacing Sanders Supporters With Paid Seat Fillers to Create Fake Unity https://t.co/dOQpqVruV…”. Tweets like these targeted Bernie supporters who were suspicious of the DNC’s disapproval of Bernie. Generally, these trolls retweeted posts that aimed to steer voters away from Hillary Clinton and towards other candidates: “RT @Tevorbowles: @PrisonPlanet @DrJillStein Please urge your supporters to go to Trump then Ms. Stein. Hillary is a dangerous sociopath.”
In order to more closely investigate the bots’ strategies, we removed all the real accounts from this graph and examined only the trolls’ interactions with one another. One thing becomes immediately clear in this graph— most trolls did not mention other trolls. More specifically, only 27% of the trolls interacted with other trolls.
One of the nodes that stands out particularly well in this graph is @ten_gop. In all of the graphs that included real users, @ten_gop did not seem to be of particular significance. However, in this graph, we can see that @ten_gop was able to reach a wide audience through other trolls— likely creating perceived social proof for @ten_gop’s ideas. As detailed by the Russia Tweets Projects, this fake account garnered over 145,000 followers, and its backup account @10_gop was retweeted by @realdonaldtrump himself.
In addition to @ten_gop, we notice another interesting fake account when we visualize the full mentioned network with all accounts and edges. Notice how the single bot @ameliebaldwin connects a swath of real users to the central cluster of bots. This account is the most connected troll in the full graph. Upon taking a closer look, we found that this bot took the approach of mentioning many real accounts a few times each. Other bots follow a similar pattern, but @ameliebaldwin is the clear front-runner here based on sheer volume of mentions. Notice this interesting contrast between @ten_gop and @ameliebaldwin. @ameliebaldwin is not very noticeable in its interactions with other trolls (see the trolls-only network), but is very noticeable in its interactions with real users. On the contrary, @ten_gop is more prominent in the trolls-only network, and it actively mentions and is mentioned by other trolls.However, @ten_gop is not as prominent in networks that contain both real and troll accounts.