Albert-Lindqvist, Torben Oskar

Bendsen, Marius Venø

Derczynski, Leon

Inie, Nanna

Pedersen, Jens Egholm

Pedersen, Viktor Due

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

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Misinformation on Twitter During the Danish National Election: A Case Study

https://pure.itu.dk/ws/files/84747296/paper_16.pdf

Misinformation on Twitter During the Danish National Election: A Case Study

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