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

Leon Derczynski, Torben Oskar Albert-Lindqvist, Marius Venø Bendsen, Nanna Inie, Jens Egholm Pedersen, Viktor Due Pedersen

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


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.
Original languageEnglish
Title of host publicationProceedings of the conference on Truth and Trust Online
Publication date4 Oct 2019
Publication statusPublished - 4 Oct 2019
EventTruth and Trust Online - London, United Kingdom
Duration: 4 Oct 20195 Oct 2019
Conference number: 1


ConferenceTruth and Trust Online
Country/TerritoryUnited Kingdom
Internet address


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