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Opinions are Made to be Changed: Temporally Adaptive Stance Classification., , and . OASIS@HT, page 27-32. ACM, (2021)Stance Classification for Rumour Verification in Social Media Conversations., , and . ICWSM Workshops, (2020)Evaluating the generalisability of neural rumour verification models., , , , , , , , and . Inf. Process. Manag., 60 (1): 103116 (2023)QMUL-SDS at CheckThat! 2020 Determining COVID-19 Tweet Check-Worthiness Using an Enhanced CT-BERT with Numeric Expressions., , , , and . CLEF (Working Notes), volume 2696 of CEUR Workshop Proceedings, CEUR-WS.org, (2020)Learning Disentangled Latent Topics for Twitter Rumour Veracity Classification., , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 3902-3908. Association for Computational Linguistics, (2021)Some Observations on Fact-Checking Work with Implications for Computational Support., , , , , , and . CoRR, (2023)Cost-Sensitive BERT for Generalisable Sentence Classification with Imbalanced Data., , and . CoRR, (2020)Building for Tomorrow: Assessing the Temporal Persistence of Text Classifiers., , and . CoRR, (2022)Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling., , , , , , and . CoRR, (2023)Rumour stance and veracity classification in social media conversations.. University of Warwick, Coventry, UK, (2019)British Library, EThOS.