Abstract

We present in this paper our participation to the task of fake news conspiracy theories detection from tweets. We rely on a variant of BERT-based classification approach to devise a first classification method for the three different tasks. Moreover, we propose a multitask learning approach to perform the three different tasks at once. Finally, we developed a prompt-based approach to generate classifications thanks to a TinyBERT pre-trained model. Our experimental results show the multitask model to be the best on the three tasks.

Citation: Cheikh Brahim El Vaigh, Thomas Girault, Cyrielle Mallart, and Duc Hau Nguyen. Detecting Fake News Conspiracies with Multitask and Prompt-Based Learning. In Workshop MediaEval Multimedia Evaluation Benchmark, 2021.
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