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.
|Titel||Proceedings of the conference on Truth and Trust Online|
|Publikationsdato||4 okt. 2019|
|Status||Udgivet - 4 okt. 2019|
|Begivenhed||Truth and Trust Online - London, Storbritannien|
Varighed: 4 okt. 2019 → 5 okt. 2019
Konferencens nummer: 1