TY - CHAP A1 - Nakov, Preslav A1 - Da San Martino, Giovanni A1 - Elsayed, Tamer A1 - Barrón-Cedeño, Alberto A1 - Míguez, Rúben A1 - Shaar, Shaden A1 - Alam, Firoj A1 - Haouari, Fatima A1 - Hasanain, Maram A1 - Babulkov, Nikolay A1 - Nikolov, Alex A1 - Shahi, Gautam Kishore A1 - Struß, Julia Maria A1 - Mandl, Thomas T1 - The CLEF-2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News T2 - Advances in Information Retrieval N2 - We describe the fourth edition of the CheckThat! Lab, part of the 2021 Cross-Language Evaluation Forum (CLEF). The lab evaluates technology supporting various tasks related to factuality, and it is offered in Arabic, Bulgarian, English, and Spanish. Task 1 asks to predict which tweets in a Twitter stream are worth fact-checking (focusing on COVID-19). Task 2 asks to determine whether a claim in a tweet can be verified using a set of previously fact-checked claims. Task 3 asks to predict the veracity of a target news article and its topical domain. The evaluation is carried out using mean average precision or precision at rank k for the ranking tasks, and F1 for the classification tasks. KW - Fake news KW - Fact-checking KW - Falschmeldung KW - Desinformation KW - Fehlinformation Y1 - 2021 SN - 978-3-030-72240-1 U6 - https://doi.org/10.1007/978-3-030-72240-1_75 SP - 639 EP - 649 PB - Springer CY - Cham ER - TY - CHAP A1 - Nakov, Preslav A1 - Da San Martino, Giovanni A1 - Elsayed, Tamer A1 - Barrón-Cedeño, Alberto A1 - Míguez, Rubén A1 - Shaar, Shaden A1 - Alam, Firoj A1 - Haouari, Fatima A1 - Hasanain, Maram A1 - Mansour, Watheq A1 - Hamdan, Bayan A1 - Sheikh Ali, Zien A1 - Babulkov, Nikolay A1 - Nikolov, Alex A1 - Koshore Shahi, Gautam A1 - Struß, Julia Maria A1 - Mandl, Thomas A1 - Kutlu, Mucahid A1 - Selim Kartal, Yavuz T1 - Overview of the CLEF–2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News T2 - Experimental IR Meets Multilinguality, Multimodality, and Interaction N2 - We describe the fourth edition of the CheckThat! Lab, part of the 2021 Conference and Labs of the Evaluation Forum (CLEF). The lab evaluates technology supporting tasks related to factuality, and covers Arabic, Bulgarian, English, Spanish, and Turkish. Task 1 asks to predict which posts in a Twitter stream are worth fact-checking, focusing on COVID-19 and politics (in all five languages). Task 2 asks to determine whether a claim in a tweet can be verified using a set of previously fact-checked claims (in Arabic and English). Task 3 asks to predict the veracity of a news article and its topical domain (in English). The evaluation is based on mean average precision or precision at rank k for the ranking tasks, and macro-F1 for the classification tasks. This was the most popular CLEF-2021 lab in terms of team registrations: 132 teams. Nearly one-third of them participated: 15, 5, and 25 teams submitted official runs for tasks 1, 2, and 3, respectively. KW - Fact-checking KW - Check-worthiness estimation KW - Desinformation KW - Fehlinformation Y1 - 2021 SN - 978-3-030-85251-1 U6 - https://doi.org/10.1007/978-3-030-85251-1_19 SP - 264 EP - 291 PB - Springer CY - Cham ER - TY - CHAP A1 - Struß, Julia Maria A1 - Ruggeri, Federico A1 - Barrón-Cedeño, Alberto A1 - Alam, Firoj A1 - Dimitrov, Dimitar A1 - Galassi, Andrea A1 - Pachov, Georgi A1 - Koychev, Ivan A1 - Nakov, Preslav A1 - Siegel, Melanie A1 - Wiegand, Michael A1 - Hasanain, Maram A1 - Suwaileh, Reem A1 - Zaghouani, Wajdi ED - Faggioli, Guglielmo ED - Ferro, Nicola ED - Galuščáková, Petra ED - Seco de Herrera, Alba García T1 - Overview of the CLEF-2024 CheckThat! Lab Task 2 on Subjectivity in News Articles BT - Notebook for the CheckThat! Lab at CLEF 2024 T2 - CLEF 2024 Working Notes : Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024) N2 - We present an overview of Task 2 of the seventh edition of the CheckThat! lab at the 2024 iteration of the Conference and Labs of the Evaluation Forum (CLEF). The task focuses on subjectivity detection in news articles and was o ered in five languages: Arabic, Bulgarian, English, German, and Italian, as well as in a multilingual setting. The datasets for each language were carefully curated and annotated, comprising over 10,000 sentences from news articles. The task challenged participants to develop systems capable of distinguishing between subjective statements (refecting personal opinions or biases) and objective ones (presenting factual information) at the sentence level. A total of 15 teams participated in the task, submitting 36 valid runs across all language tracks. The participants used a variety of approaches, with transformer-based models being the most popular choice. Strategies included fine-tuning monolingual and multilingual models, and leveraging English models with automatic translation for the non-English datasets. Some teams also explored ensembles, feature engineering, and innovative techniques such as few-shot learning and in-context learning with large language models. The evaluation was based on macro-averaged F1 score. The results varied across languages, with the best performance achieved for Italian and German, followed by English. The Arabic track proved particularly challenging, with no team surpassing an F1 score of 0.50. This task contributes to the broader goal of enhancing the reliability of automated content analysis in the context of misinformation detection and fact-checking. The paper provides detailed insights into the datasets, participant approaches, and results, o ering a benchmark for the current state of subjectivity detection across multiple languages. KW - Fehlinformation KW - Zeitungsartikel Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0074-3740-3 UR - https://ceur-ws.org/Vol-3740/paper-25.pdf SN - 1613-0073 SP - 287 EP - 298 CY - Frankreich ER - TY - CHAP A1 - Barrón-Cedeño, Alberto A1 - Alam, Firoj A1 - Chakraborty, Tonmoy A1 - Elsayed, Tamer A1 - Nakov, Preslav A1 - Przybyła, Piotr A1 - Struß, Julia Maria A1 - Haouari, Fatima A1 - Hasanain, Maram A1 - Ruggeri, Federico A1 - Song, Xingyi A1 - Suwaileh, Reem ED - Goharian, Nazli ED - Tonellotto, Nicola ED - He, Yulan ED - Lipani, Aldo ED - McDonald, Graham ED - Macdonald, Craig ED - Ounis, Iadh T1 - The CLEF-2024 CheckThat! Lab BT - Check-Worthiness, Subjectivity, Persuasion, Roles, Authorities, and Adversarial Robustness T2 - Advances in Information Retrieval N2 - The first five editions of the CheckThat! lab focused on the main tasks of the information verification pipeline: check-worthiness, evidence retrieval and pairing, and verification. Since the 2023 edition, it has been focusing on new problems that can support the research and decision making during the verification process. In this new edition, we focus on new problems and -for the first time- we propose 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 estimation of check-worthiness (the only task that has been present in all CheckThat! editions), Task 2 identification of subjectivity (a follow up of CheckThat! 2023 edition), Task 3 identification of persuasion (a follow up of SemEval 2023), Task 4 detection of hero, villain, and victim from memes (a follow up of CONSTRAINT 2022), Task 5 Rumor Verification using Evidence from Authorities (a first), and Task 6 robustness of credibility assessment with adversarial examples (a first). These tasks represent challenging classification and retrieval problems at the document and at the span level, including multilingual and multimodal settings. KW - Desinformation KW - Subjektivität KW - Bias KW - Faktizität Y1 - 2024 SN - 978-3-031-56069-9 U6 - https://doi.org/10.1007/978-3-031-56069-9_62 SN - 0302-9743 SP - 449 EP - 458 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Barrón-Cedeño, Alberto A1 - Alam, Firoj A1 - Struß, Julia Maria A1 - Nakov, Preslav A1 - Chakraborty, Tanmoy A1 - Elsayed, Tamer A1 - Przybyła, Piotr A1 - Caselli, Tommaso A1 - Da San Martino, Giovanni A1 - Haouari, Fatima A1 - Hasanain, Maram A1 - Li, Chengkai A1 - Piskorski, Jakub A1 - Ruggeri, Federico A1 - Song, Xingyi A1 - Suwaileh, Reem ED - Goeuriot, Lorraine ED - Mulhem, Philippe ED - Quénot, Georges ED - Schwab, Didier ED - Di Nunzio, Giorgio Maria ED - Soulier, Laure ED - Galušcáková, Petra ED - Seco de Herrera, Alba García ED - Faggioli, Guglielmo ED - Ferro, Nicola T1 - Overview of the CLEF-2024 CheckThat! Lab : Check-Worthiness, Subjectivity, Persuasion, Roles, Authorities, and Adversarial Robustness T2 - 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 N2 - 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. KW - Desinformation KW - Fehlinformation Y1 - 2024 SN - 978-3-031-71907-3 U6 - https://doi.org/10.1007/978-3-031-71908-0 SP - 28 EP - 52 PB - Springer Nature CY - Berlin ER - TY - CHAP A1 - Barrón-Cedeño, Alberto A1 - Alam, Firoj A1 - Galassi, Andrea A1 - Da San Martino, Giovanni A1 - Nakov, Preslav A1 - Elsayed, Tamer A1 - Azizov, Dilshod A1 - Caselli, Tommaso A1 - Cheema, Gullal S. A1 - Haouari, Fatima A1 - Hasanain, Maram A1 - Kutlu, Mucahid A1 - Li, Chengkai A1 - Ruggeri, Federico A1 - Struß, Julia Maria A1 - Zaghouani, Wajdi ED - Arampatzis, Avi ED - Kanoulas, Evangelos ED - Tsikrika, Theodora ED - Vrochidis, Stefanos ED - Giachanou, Anastasia ED - Li, Dan ED - Aliannejadi, Mohammad ED - Vlachos, Michalis ED - Faggioli, Guglielmo ED - Ferro, Nicola T1 - Overview of the CLEF–2023 CheckThat! Lab on Checkworthiness, Subjectivity, Political Bias, Factuality, and Authority of News Articles and Their Source T2 - Experimental IR Meets Multilinguality, Multimodality, and Interaction N2 - We describe the sixth edition of the CheckThat! lab, part of the 2023 Conference and Labs of the Evaluation Forum (CLEF). The five previous editions of CheckThat! focused on the main tasks of the information verification pipeline: check-worthiness, verifying whether a claim was fact-checked before, supporting evidence retrieval, and claim verification. In this sixth edition, we zoom into some new problems and for the first time we offer five tasks in seven languages: Arabic, Dutch, English, German, Italian, Spanish, and Turkish. Task 1 asks to determine whether an item - text or text plus image- is check-worthy. Task 2 aims to predict whether a sentence from a news article is subjective or not. Task 3 asks to assess the political bias of the news at the article and at the media outlet level. Task 4 focuses on the factuality of reporting of news media. Finally, Task 5 looks at identifying authorities in Twitter that could help verify a given target claim. For a second year, CheckThat! was the most popular lab at CLEF-2023 in terms of team registrations: 127 teams. About one-third of them (a total of 37) actually participated. KW - Desinformation KW - Fehlinformation KW - COVID-19 Y1 - 2023 SN - 978-3-031-42448-9 U6 - https://doi.org/10.1007/978-3-031-42448-9_20 SN - 1611-3349 SP - 251 EP - 275 PB - Springer International Publishing CY - Cham ER - TY - CHAP A1 - Galassi, Andrea A1 - Ruggeri, Federico A1 - Barrón-Cedeño, Alberto A1 - Alam, Firoj A1 - Caselli, Tommaso A1 - Kutlu, Mucahid A1 - Struß, Julia Maria A1 - Antici, Francesco A1 - Hasanain, Maram A1 - Köhler, Juliane A1 - Korre, Katerina A1 - Leistra, Folkert A1 - Muti, Arianna A1 - Siegel, Melanie A1 - Türkmen, Mehmet Deniz A1 - Wiegand, Michael A1 - Zaghouani, Wajdi ED - Aliannejadi, Mohammad ED - Faggiolo, Guglielmo ED - Ferro, Nicola ED - Vlachos, Michalis T1 - Overview of the CLEF-2023 CheckThat! Lab: Task 2 on Subjectivity in News Articles BT - Notebook for the CheckThat! Lab at CLEF 2023 T2 - CLEF 2023 Working Notes N2 - We describe the outcome of the 2023 edition of the CheckThat!Lab at CLEF. We focus on subjectivity (Task 2), which has been proposed for the first time. It aims at fostering the technology for the identification of subjective text fragments in news articles. For that, we produced corpora consisting of 9,530 manually-annotated sentences, covering six languages - Arabic, Dutch, English, German, Italian, and Turkish. Task 2 attracted 12 teams, which submitted a total of 40 final runs covering all languages. The most successful approaches addressed the task using state-of-the-art multilingual transformer models, which were fine-tuned on language-specific data. Teams also experimented with a rich set of other neural architectures, including foundation models, zero-shot classifiers, and standard transformers, mainly coupled with data augmentation and multilingual training strategies to address class imbalance. We publicly release all the datasets and evaluation scripts, with the purpose of promoting further research on this topic. KW - Desinformation KW - Fehlinformation KW - COVID-19 Y1 - 2023 UR - https://ceur-ws.org/Vol-3497/paper-020.pdf SP - 236 EP - 249 CY - Thessaloniki ER -