Leon Derczynski, Torben Oskar Albert-Lindqvist, Marius Venø Bendsen, Nanna Inie, Viktor Due Pedersen and Jens Egholm Pedersen
TRUTH & TRUST ONLINE 2019
Elections are a time when communication is important in democracies, including over social media. This paper describes a case study of applying NLP to determine the extent to which misinformation and external manipulation were present on Twitter during a national election. We use three methods to detect the spread of misinformation: analysing unusual spatial and temporal behaviours; detecting known false claims and using these to estimate the total prevalence; and detecting amplifiers through language use. We find that while present, detectable spread of misinformation on Twitter was remarkably low during the election period in Denmark.