Information disorders, such as dis-, mis-, and malinformation, can lead to societal and economic harm. They are rapidly spread, extensively consumed on the web, and represent a threat to democracy. The aim of this work is to better understand the state of the art regarding information disorder detection approaches by conducting a reproducibility study and a cross-data and cross-model comparative analysis. we provide takeaways concerning reproducibility and stress the need for better AI detection
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