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Title: Fight Against Misinformation on Social Media: Detecting Attention-Worthy and Harmful Tweets and Verifiable and Check-Worthy Claims
Authors: Eyuboglu, A.B.
Altun, B.
Arslan, M.B.
Sonmezer, E.
Kutlu, M.
Keywords: Attention-worthy tweets
Factual Claims
Harmful tweets
Computational linguistics
Attention-worthy tweet
Factual claim
Fine tuning
Harmful tweet
Social media
Transformer modeling
Social networking (online)
Issue Date: 2023
Publisher: Springer Science and Business Media Deutschland GmbH
Abstract: In this paper, we present our participation in CLEF 2022 CheckThat! Lab’s Task 1 on detecting check-worthy and verifiable claims and attention-worthy and harmful tweets. We participated in all subtasks of Task 1 for Arabic, Bulgarian, Dutch, English, and Turkish datasets. We investigate the impact of fine-tuning various transformer models and how to increase training data size using machine translation. We also use feed-forward networks with the Manifold Mixup regularization for the respective tasks. We are ranked first in detecting factual claims in Arabic and harmful tweets in Dutch. In addition, we are ranked second in detecting check-worthy claims in Arabic and Bulgarian. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Description: Proceedings of the 14th International Conference of the Cross-Language Evaluation Forum for European Languages, CLEF 2023 -- 18 September 2023 through 21 September 2023 -- 300519
ISBN: 9783031424472
ISSN: 0302-9743
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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