@inproceedings{BarronCedenoAlamStrussetal., author = {Barr{\´o}n-Cede{\~n}o, Alberto and Alam, Firoj and Struß, Julia Maria and Nakov, Preslav and Chakraborty, Tanmoy and Elsayed, Tamer and Przybyła, Piotr and Caselli, Tommaso and Da San Martino, Giovanni and Haouari, Fatima and Hasanain, Maram and Li, Chengkai and Piskorski, Jakub and Ruggeri, Federico and Song, Xingyi and Suwaileh, Reem}, title = {Overview of the CLEF-2024 CheckThat! Lab : Check-Worthiness, Subjectivity, Persuasion, Roles, Authorities, and Adversarial Robustness}, series = {Experimental IR Meets Multilinguality, Multimodality, and Interaction : 15th International Conference of the CLEF Association, CLEF 2024, Grenoble, France, September 9-12, 2024, Proceedings, Part II}, booktitle = {Experimental IR Meets Multilinguality, Multimodality, and Interaction : 15th International Conference of the CLEF Association, CLEF 2024, Grenoble, France, September 9-12, 2024, Proceedings, Part II}, editor = {Goeuriot, Lorraine and Mulhem, Philippe and Qu{\´e}not, Georges and Schwab, Didier and Di Nunzio, Giorgio Maria and Soulier, Laure and Galušc{\´a}kov{\´a}, Petra and Seco de Herrera, Alba Garc{\´i}a and Faggioli, Guglielmo and Ferro, Nicola}, publisher = {Springer Nature}, address = {Berlin}, isbn = {978-3-031-71907-3}, doi = {10.1007/978-3-031-71908-0}, pages = {28 -- 52}, abstract = {We describe the seventh edition of the CheckThat! lab, part of the 2024 Conference and Labs of the Evaluation Forum (CLEF). Previous editions of CheckThat! focused on the main tasks of the information verification pipeline: check-worthiness, identifying previously fact-checked claims, supporting evidence retrieval, and claim verification. In this edition, we introduced some new challenges, offering six tasks in fifteen languages (Arabic, Bulgarian, English, Dutch, French, Georgian, German, Greek, Italian, Polish, Portuguese, Russian, Slovene, Spanish, and code-mixed Hindi-English): Task 1 on estimation of check-worthiness (the only task that has been present in all CheckThat! editions), Task 2 on identification of subjectivity (a follow up of the CheckThat! 2023 edition), Task 3 on identification of the use of persuasion techniques (a follow up of SemEval 2023), Task 4 on detection of hero, villain, and victim from memes (a follow up of CONSTRAINT 2022), Task 5 on rumor verification using evidence from authorities (new task), and Task 6 on robustness of credibility assessment with adversarial examples (new task). These are challenging classification and retrieval problems at the document and at the span level, including multilingual and multimodal settings. This year, CheckThat! was one of the most popular labs at CLEF-2024 in terms of team registrations: 130 teams. More than one-third of them (a total of 46) actually participated.}, subject = {Desinformation}, language = {en} } @inproceedings{NakovBarronCedenoDaSanMartinoetal., author = {Nakov, Preslav and Barr{\´o}n-Cede{\~n}o, Alberto and Da San Martino, Giovanni and Alam, Firoj and Struß, Julia Maria and Mandl, Thomas and M{\´i}guez, Rub{\´e}n and Caselli, Tommaso and Kutlu, Mucahid and Zaghouani, Wajdi and Li, Chengkai and Shaar, Shaden and Shahi, Gautam Kishore and Mubarak, Hamdy and Nikolov, Alex and Babulkov, Nikolay and Kartal, Yavuz Selim and Wiegand, Michael and Siegel, Melanie and K{\"o}hler, Juliane}, title = {Overview of the CLEF-2022 CheckThat! Lab on Fighting the COVID-19 Infodemic and Fake News Detection}, series = {Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2022.}, booktitle = {Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2022.}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-13643-6}, issn = {0302-9743}, doi = {10.1007/978-3-031-13643-6_29}, pages = {495 -- 520}, abstract = {We describe the fifth edition of the CheckThat! lab, part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). The lab evaluates technology supporting tasks related to factuality in multiple languages: Arabic, Bulgarian, Dutch, English, German, Spanish, and Turkish. Task 1 asks to identify relevant claims in tweets in terms of check-worthiness, verifiability, harmfullness, and attention-worthiness. Task 2 asks to detect previously fact-checked claims that could be relevant to fact-check a new claim. It targets both tweets and political debates/speeches. Task 3 asks to predict the veracity of the main claim in a news article. CheckThat! was the most popular lab at CLEF-2022 in terms of team registrations: 137 teams. More than one-third (37\%) of them actually participated: 18, 7, and 26 teams submitted 210, 37, and 126 official runs for tasks 1, 2, and 3, respectively.}, subject = {Desinformation}, language = {en} } @inproceedings{NakovBarronCedenoDaSanMartinoetal., author = {Nakov, Preslav and Barr{\´o}n-Cede{\~n}o, Alberto and Da San Martino, Giovanni and Alam, Firoj and Struß, Julia Maria and Mandl, Thomas and M{\´i}guez, Rub{\´e}n and Caselli, Tommaso and Kutlu, Mucahid and Zaghouani, Wajdi and Li, Chengkai and Shaar, Shaden and Shahi, Gautam Kishore and Mubarak, Hamdy and Nikolov, Alex and Babulkov, Nikolay and Kartal, Yavuz Selim and Beltr{\´a}n, Javier}, title = {The CLEF-2022 CheckThat! Lab on Fighting the COVID-19 Infodemic and Fake News Detection}, series = {Advances in Information Retrieval. ECIR 2022}, booktitle = {Advances in Information Retrieval. ECIR 2022}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-99739-7}, issn = {0302-9743}, doi = {10.1007/978-3-030-99739-7_52}, pages = {416 -- 428}, abstract = {The fifth edition of the CheckThat! Lab is held as part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). The lab evaluates technology supporting various factuality tasks in seven languages: Arabic, Bulgarian, Dutch, English, German, Spanish, and Turkish. Task 1 focuses on disinformation related to the ongoing COVID-19 infodemic and politics, and asks to predict whether a tweet is worth fact-checking, contains a verifiable factual claim, is harmful to the society, or is of interest to policy makers and why. Task 2 asks to retrieve claims that have been previously fact-checked and that could be useful to verify the claim in a tweet. Task 3 is to predict the veracity of a news article. Tasks 1 and 3 are classification problems, while Task 2 is a ranking one.}, subject = {Desinformation}, language = {en} }