Advertisement

Study: Russian Twitter bots sent 45k Brexit tweets close to vote

Study: Russian Twitter bots sent 45k Brexit tweets close to vote
From TechCrunch - November 15, 2017

To what extentand how successfullydid Russian backed agents use social media to influence the UKs Brexit vote?Yesterday Facebook admitted it had linked some Russian accounts to Brexit-related ad buys and/or the spread of political misinformation on its platform, though it hasnt yet disclosed how many accounts were involved or how many rubles were spent.

Today theThe Timesreported on research conducted by a group of data scientists in the US and UK looking at how information was diffused on Twitter around the June 2016 EU referendum vote, and around the 2016 US presidential election.

The Times reports that the study tracked 156,252 Russian accounts which mentioned #Brexit, and also found Russian accounts posted almost 45,000 messages pertaining to the EU referendum in the 48 hours around the vote.

Although Tho Pham, one of the report authors, confirmed to us in an email that the majority of those Brexit tweets were posted on June 24, 2016, the day after the votewhen around 39,000 Brexit tweets were posted by Russian accounts, according to the analysis.

But in the run up to the referendum vote they also generally found that human Twitter users were more likely to spread pro-leave Russian bot content via retweets (vs pro-remain content)amplifying its potential impact.

From the research paper:

During the Referendum day, there is a sign that bots attempted to spread more leave messages with positive sentiment as the number of leave tweets with positive sentiment increased dramatically on that day.

More specifically, for every 100 bots tweets that were retweeted, about 80-90 tweets were made by humans. Furthermore, before the Referendum day, among those humans retweets from bots, tweets by the Leave side accounted for about 50% of retweets while only nearly 20% of retweets had pro-remain content. In the other words, there is a sign that during pre-event period, humans tended to spread the leave messages that were originally generated by bots. Similar trend is observed for the US Election sample. Before the Election Day, about 80% of retweets were in favour of Trump while only 20% of retweets were supporting Clinton.

You do have to wonder whether Brexit wasnt something of a dry run disinformation campaign for Russian bots ahead of the US election a few months later.

The research paper, entitled Social media, sentiment and public opinions: Evidence from #Brexit and #USElection, which is authored by three data scientists from Swansea University and the University of California, Berkeley, used Twitters API to obtain relevant datasets of tweets to analyze.

After screening, their dataset for the EU referendum contained about 28.6M tweets, while the sample for the US presidential election contained ~181.6M tweets.

The researchers say they identified a Twitter account as Russian-related if it had Russian as the profile language but the Brexit tweets were in English.

While they detected bot accounts (defined by them as Twitter users displaying botlike behavior) using a method that includes scoring each account on a range of factors such as whether it tweeted at unusual hours; the volume of tweets including vs account age; and whether it was posting the same content per day.

Around the US election, the researchers generally found a more sustained use of politically motivated bots vs around the EU referendum vote (when bot tweets peaked very close to the vote itself).

They write:

First, there is a clear difference in the volume of Russian-related tweets between Brexit sample and US Election sample. For the Referendum, the massive number of Russian-related tweets were only created few days before the voting day, reached its peak during the voting and result days then dropped immediately afterwards. In contrast, Russian-related tweets existed both before and after the Election Day. Second, during the running up to the Election, the number of bots Russian-related tweets dominated the ones created by humans while the difference is not significant during other times. Third, after the Election, bots Russian-related tweets dropped sharply before the new wave of tweets was created. These observations suggest that bots might be used for specific purposes during high-impact events.

In each data set, they found bots typically more often tweeting pro-Trump and pro-leave views vs pro-Clinton and pro-remain views, respectively.

They also say they foundsimilarities in how quickly information was disseminated around each of the two events, and in how human Twitter users interacted with botswith human users tending to retweet bots that expressed sentiments they also supported. The researchers say this supports the view of Twitter creating networked echo chambers of opinion as users fix on and amplify only opinions that align with their own, avoiding engaging with different views.

Combine that echo chamber effect with deliberate deployment of politically motivated bot accounts and the platform can be used to enhance social divisions, they suggest.

From the paper:

These results lend supports to the echo chambers view that Twitter creates networks for individuals sharing the similar political beliefs. As the results, they tend to interact with others from the same communities and thus their beliefs are reinforced. By contrast, information from outsiders is more likely to be ignored. This, coupled by the aggressive use of Twitter bots during the high-impact events, leads to the likelihood that bots are used to provide humans with the information that closely matches their political views. Consequently, ideological polarization in social media like Twitter is enhanced. More interestingly, we observe that the influence of pro-leave bots is stronger the influence of pro-remain bots. Similarly, pro-Trump bots are more influential than pro-Clinton bots. Thus, to some degree, the use of social bots might drive the outcomes of Brexit and the US Election.

Advertisement

Continue reading at TechCrunch »