Junk News during the EU Parliamentary Elections

Access to accurate information about politics and electoral processes is critical to the health of democratic systems. With this in mind, this data memo examines the quality and quantity of political news and information that social media users were sharing across seven European languages (English, French, German, Italian, Polish, Spanish, and Swedish) in the lead-up to the 2019 European parliamentary elections.

We collected 584,062 tweets related to the European parliamentary elections from 187,743 unique users between 5 April and 20 April using election-related hashtags. From this sample, we extracted 137,658 tweets containing a URL link, which pointed to a total of 5,774 unique media sources. Sources that were shared five times or more across our collection period were manually classified by a team of nine multi-lingual coders based on a rigorous grounded typology developed and refined through the project’s previous studies of eight elections.

To provide a snapshot of public engagement with sources of misinformation shared ahead of the European elections, we extracted the five most popular sources of junk news in each language sphere and measured the volume of Facebook interactions with these outlets in the month preceding the election (5 April–5 May) using the NewsWhip Analytics dashboard. As points of comparison, we computed the same metrics for the five most popular professional news sources from each language sphere. Finally, to gain a better understanding of the different political narratives favoured by junk news outlets, we conducted a thematic analysis of the 20 most engaging junk news stories on Facebook during our data collection period.

Our main findings are:

Less than 4% of sources circulating on Twitter during our data collection period were junk news or known Russian sources, with users sharing far more links to mainstream news outlets overall (34%), except in the Polish sphere, where junk news made up 21% of traffic.

On Facebook, while many more users interact with mainstream content overall, individual junk news stories can still hugely outperform even the best, most important professionally produced stories, drawing as much as four times the volume of shares, likes, and comments.

The most successful junk news stories in our data set tend to revolve around populist themes such as anti-immigration and Islamophobic sentiment, with few expressing Euroscepticism or directly mentioning European leaders or parties.

Read the full data memo here.

Read the data supplement here.

To track what kinds of junk news are circulating in the EU, have a look at our junk news aggregator.

Nahema Marchal, Bence Kollanyi, Lisa-Maria Neudert, Philip N. Howard. “Junk News During the EU Parliamentary Elections: Lessons from a Seven-Language Study of Twitter and Facebook.” Data Memo 2019.3. Oxford, UK: Project on Computational Propaganda. comprop.oii.ox.ac.uk

The full list of Tweet IDs for Tweets analysed in this study is available on our replication data page.