Tuesday 24 April 2018

Funded PhD Opportunity: Large Scale Analysis of Online Disinformation in Political Debates

Applications are invited for an EPSRC-funded studentship at The University of Sheffield commencing on 1 October 2018.

The PhD project will examine the intersection of online political debates and misinformation, through big data analysis. This research is very timely, because online mis- and disinformation is reinforcing the formation of polarised partisan camps, sharing biased, self-reinforcing content. This is coupled with the rise in post-truth politics, where key arguments are repeated continuously, even when proven untrue by journalists or independent experts. Journalists and media have tried to counter this through fact-checking initiatives, but these are currently mostly manual, and thus not scalable to big data.


The aim is to develop machine learning-based methods for large-scale analysis of online misinformation and its role in political debates on online social platforms.



Application deadline: as soon as possible, until the funding is filled  
Interviews: interviews take place within 2-3 weeks of application

Supervisory team: Professor Kalina Bontcheva (Department of Computer Science, University of Sheffield), Professor Piers Robinson (Department of Journalism, University of Sheffield), and Dr. Nikolaos Aletras (Information School, University of Sheffield).


Award Details

The studentship will cover tuition fees at the EU/UK rate and provide an annual maintenance stipend at standard Research Council rates (£14,777 in 2018/19) for 3.5 years.

Eligibility

The general eligibility requirements are:
  • Applicants should normally have studied in a relevant field to a very good standard at MSc level or equivalent experience.
  • Applicants should also have a 2.1 in a BSc degree, or equivalent qualification, in a related discipline.
  • ESRPC studentships are only available to students from the UK or European Union. Applications cannot be accepted from students liable to pay fees at the Overseas rate. Normally UK students will be eligible for a full award which pays fees and a maintenance grant if they meet the residency criteria and EU students will be eligible for a fees-only award, unless they have been resident in the UK for 3 years immediately prior to taking up the award.

How to apply

To apply for the studentship, applicants need to apply directly to the University of Sheffield for entrance into the doctoral programme in Computer Science 


  • Complete an application for admission to the standard computer science PhD programme http://www.sheffield.ac.uk/postgraduate/research/apply 
  • Applications should include a research proposal; CV; academic writing sample; transcripts and two references.
  • The research proposal of up to 1,000 words should outline your reasons for applying to this project and how you would approach the research including details of your skills and experience in both computing and/or data journalism.
  • Supporting documents should be uploaded to your application.

Sunday 8 April 2018

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
.
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.

Discerning Truth in the Age of Ubiquitous Disinformation (4): Russian Involvement in the Referendum and the Impact of Social Media Misinformation on Voting Behaviour

Discerning Truth in the Age of Ubiquitous Disinformation (4)

Russian Involvement in the Referendum and the Impact of Social Media Misinformation on Voting Behaviour


Kalina Bontcheva (@kbontcheva)


In my previous blog posts I wrote about the 4Ps of the modern disinformation age: post-truth politics, online propaganda, polarised crowds,  and partisan media; and how we can combat online disinformation


The news is currently full of reports of Russian involvement in the referendum and the potential impact of social media misinformation on voting behaviour

A small scale experiment by the Guardian exposed 10 US voters (five on each side) to  alternative Facebook news feeds. Only one participant changed his mind as to how they would vote. Some found their confirmation bias too hard to overcome, while others became acutely aware of being the target of abuse, racism, and misogyny.  A few started empathising with voters holding opposing views. They also gained awareness of the fact that opposing views abound on Facebook, but the platform is filtering them out. 


Russian Involvement in the Referendum


We analysed the accounts that were identified by Twitter as being associated with Russia in front of the US Congress in the fall of 2017, and we also took the other 45 ones that we found with BuzzFeed. We looked at tweets posted by these accounts one month before the referendum, and we did not find an awful lot of activity when compared to the overall number of tweets on the referendum, i.e. both the Russia-linked ads and Twitter accounts did not have major influence. 

There were 3,200 tweets in our data sets coming from those accounts, and 800 of those—about 26%—came from the new 45 accounts that we identified. However, one important aspect that has to be mentioned is that those 45 new accounts were tweeting in German, so even though they are there, the likely impact of those 800 tweets on the British voter is, I would say, not very likely to have been significant.

The accounts that tweeted on 23 Jun were quite different from those that tweeted before or after, with virtually all tweets posted in German. Their behaviour is also very different - with mostly retweets on referendum day by a tight network of anti-Merkel accounts, often within seconds of each other. The findings are in line with those of Prof. Cram from the University of Edinburgh, as reported in the Guardian

Journalists from BuzzFeed UK and our Sheffield  team  used the re-tweet  network to identify another 45 suspicious accounts, subsequently suspended by Twitter. Amongst the 3,200 total tweets, 830 came from the 45 newly identified accounts (26%).  Similar to those identified by Twitter, the newly discovered accounts were largely ineffective in skewing public debate. They attracted very few likes and retweets – the most successful message in the sample got just 15 retweets.

An important distinction that needs to be made is between Russia-influenced accounts that used advertising on one hand, and the Russia-related bots found by Twitter and other researchers on the other. 

The Twitter sockpuppet/bot accounts generally pretended to be authentic people (mostly American, some German) and would not resort to advertising, but instead try to go viral or gain prominence through interactions. An example of one such successful account/cyborg is Jenn_Abrams. Here are some details on how the account duped mainstream media:

http://amp.thedailybeast.com/jenna-abrams-russias-clown-troll-princess-duped-the-mainstream-media-and-the-world 

“and illustrates how Russian talking points can seep into American mainstream media without even a single dollar spent on advertising.”

https://www.theguardian.com/technology/shortcuts/2017/nov/03/jenna-abrams-the-trump-loving-twitter-star-who-never-really-existed 

http://money.cnn.com/2017/11/17/media/new-jenna-abrams-account-twitter-russia/index.html 

A related question is the influence of Russia-sponsored media and its Twitter posts. Here we consider the Russia Today promoted tweets - the 3 pre-referendum ones attracted just 53 likes and 52 retweets between them.

We analysed all tweets posted one month before 23 June 2016, which are either authored by Russia Today or Sputnik, or are retweets of these. This gives an indication of how much activity and engagement there was around these accounts. To put these numbers in context, we also included the equivalent statistics for the two main pro-leave and pro-remain Twitter accounts:



Account
Original tweets
Retweeted by others
Retweets by this account
Replies by account
Total tweets
@RT_com -  General Russia Today
39
2,080 times
62
0
2,181
@RTUKnews
78
2,547 times
28
1
2,654
@SputnikInt
148
1,810 times
3
2
1,963
@SputnikNewsUK
87
206 times
8
4
305
TOTAL
352
6,643
101
7
7,103






@Vote_leave
2,313
231,243
1,399
11
234,966
@StrongerIn
2,462
132,201
910
7
135,580


We also analysed which accounts retweeted RT_com and RTUKnews the most in our dataset. The top one with 75 retweets of Russia Today tweets was a self-declared US-based account that retweets Alex Jones from infowars, RT_com, China Xynhua News, Al Jazeera, and an Iranian news account. This account (still live) joined in Feb 2009 and as of 15 December 2017 has 1.09 million tweets - this means an average of more than 300 tweets per day, indicating it is a highly automated account. It has more than 4k followers, but follows only 33 accounts. Two of the next most active retweeters are a deleted and a suspended account, as well as two accounts that both stopped tweeting on 18 Sep 2016. 

For the two Sputnik accounts, the top retweeter made 65 retweets. It declares itself as Ireland based; has 63.7k tweets and 19.6k likes; many self-authored tweets; last active on 2 May 2017; account created on May 2015; avg 87 tweets a day (which possibly indicates an automated account);. It also retweeted Russia Today 15 times. The next two Sputnik retweeters (61 and 59 retweets respectively) are accounts with high average post-per-day rate (350 and 1,000 respectively) and over 11k and 2k followers respectively. Lastly, four of the top 10 accounts have been suspended or deleted. 



Disclaimer: All views are my own.