Discerning Truth in the Age of Ubiquitous Disinformation (5): Impact of Russia-linked Misinformation vs Impact of False Claims Made By Politicians During the Referendum Campaign

Discerning Truth in the Age of Ubiquitous Disinformation (5)

Impact of Russia-linked Misinformation vs Impact of False Claims Made By Politicians During the Referendum Campaign

Kalina Bontcheva (@kbontcheva)


My previous post focuses mainly on the impact of misinformation from Russian Twitter accounts.  However it is important to also acknowledge the impact of false claims made by politicians which were shared and distributed through social media.

A House of Commons Treasury Committee Report published on May 2016, states that: “The public debate is being poorly served by inconsistent, unqualified and, in some cases, misleading claims and counter-claims. Members of both the ‘leave’ and ‘remain’ camps are making such claims. Another aim of this report is to assess the accuracy of some of these claims..”

In our research, we analysed the number of Twitter posts around some of the these disputed claims, firstly to understand their resonance with voters, and secondly, to compare this to the volume of Russia-related tweets discussed above.

A study  of the news coverage of the EU Referendum campaign established that the economy was the most covered issue, and in particular, the Remain claim that Brexit would cost households £4,300 per year by 2030 and the Leave campaign’s claim that the EU cost the UK £350 million each week. Therefore, we focused on  these two key claims and analysed tweets about them.

With respect to the disputed £4,300 claim (made by the Chancellor of the Exchequer), we  identified 2,404 posts in our dataset (tweets, retweets, replies), referring to this claim.

For the £350 million a week disputed claim - there are 32,755 pre-referendum posts (tweets, retweets, replies) in our dataset. This is 4.6 times the 7,103 posts related to Russia Today and Sputnik and 10.2 times more than the 3,200 tweets by the Russia-linked accounts suspended by Twitter.

In particular, there are more than 1,500 tweets from different voters, with one of these wordings:

I am with @Vote_leave because we should stop sending £350 million per week to Brussels, and spend our money on our NHS instead.

I just voted to leave the EU by postal vote! Stop sending our tax money to Europe, spend it on the NHS instead! #VoteLeave #EUreferendum

Many of those tweets have themselves received over a hundred likes and retweets each.

This false claim is being regarded by media as one of the key ones behind the success of VoteLeave.

So returning to Q27 on likely impact of misinformation on voting behaviour - it was not possible for us to quantify this from such tweets alone. A potentially useful indicator comes from an Ipsos Mori poll published on 22 Jun 2016, which  showed that for 9% of respondents the NHS was the most important issue in the campaign.


In conclusion, while it is important to quantify the potential impact of Russian misinformation, we should also consider the much wider range of misinformation that was posted on Twitter and Facebook during the referendum and its likely overall impact.

We should also study not just fake news sites and the social platforms that were used to disseminate misinformation, but also the role and impact of Facebook-based algorithms for micro-targeting adverts, that have been developed by private third parties.

A related question, is studying the role played by hyperpartisan and mainstream media sites during the referendum campaign. This is the subject of our latest study, with key findings available here
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High Automation Accounts in Our Brexit Tweet Dataset

While it is hard to quantify all different kinds of fake accounts, we know already that a study by City University identified 13,493 suspected bot accounts, amongst which Twitter found only 1% as being linked to Russia. In our referendum tweet dataset there are tweets by 1,808,031 users in total, which makes the City bot accounts only 0.74% of the total.

If we consider in particular, Twitter accounts that have posted more than 50 times a day (considered high automation accounts by researchers), then there are only 457 such users in the month leading up to the referendum on 3 June 2016.

The most prolific were "ivoteleave" and "ivotestay", both suspended, which were similar in usage pattern. There were also a lot of accounts that did not really seem to post much about Brexit but were using the hashtags in order to get attention for commercial reasons.

We also analysed the leaning of these 457 high automation accounts an identified 361 as pro-leave (with 1,048,919 tweets), 39 pro-remain (156,331 tweets), and the remaining 57 as undecided.

I covered how we can address the “fake news” problem in me previous blog post (link) but in summary we need to promote fact checking efforts, and fund open-source research on automatic methods for disinformation detection.

Disclaimer: All views are my own.