Too many claims to fact-check: Prioritizing political claims based on check-worthiness

Abstract

The massive amount of misinformation spreading on the Internet on a daily basis has enormous negative impacts on societies. Therefore, we need automated systems helping fact-checkers in the combat against misinformation. In this paper, we propose a model prioritizing the claims based on their check-worthiness. We use BERT model with additional features including domain-specific controversial topics, word embeddings, and others. In our experiments, we show that our proposed model outperforms all state-of-the-art models in both test collections of CLEF Check That! Lab in 2018 and 2019. We also conduct a qualitative analysis to shed light detecting check-worthy claims. We suggest requesting rationales behind judgments are needed to understand subjective nature of the task and problematic labels. © 2020 CEUR-WS. All rights reserved.