Forskning ved Københavns Universitet - Københavns Universitet

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KU-CST at the Profiling Fake News spreaders Shared Task---Notebook for PAN at CLEF 2020

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

In this document we present our approach for profiling fake news spreaders. The model relies on semantic features, part-of-speech tag related features and other simple features. We have reached an accuracy of 0.697 and 0.810 for English and Spanish, respectively, on validation data. Test accuracies using these same models reach 0.690 and 0.725 for English and Spanish data. We believe that this is a simple and robust model that could potentially be used as a baseline for this task.
OriginalsprogEngelsk
TitelCLEF 2020 Labs and Workshops, Notebook Papers : CEUR-WS.org
Antal sider5
ForlagCEUR-WS.org
Publikationsdato2020
StatusUdgivet - 2020

ID: 248898923