Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/9011
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Nakov P. | - |
dc.contributor.author | Barrón-Cedeño A. | - |
dc.contributor.author | Da San Martino G. | - |
dc.contributor.author | Alam F. | - |
dc.contributor.author | Míguez R. | - |
dc.contributor.author | Caselli T. | - |
dc.contributor.author | Kartal Y.S. | - |
dc.date.accessioned | 2022-11-30T19:26:28Z | - |
dc.date.available | 2022-11-30T19:26:28Z | - |
dc.date.issued | 2022 | - |
dc.identifier.issn | 1613-0073 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/9011 | - |
dc.description | 2022 Conference and Labs of the Evaluation Forum, CLEF 2022 -- 5 September 2022 through 8 September 2022 -- -- 181762 | en_US |
dc.description.abstract | We present an overview of CheckThat! lab 2022 Task 1, part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). Task 1 asked to predict which posts in a Twitter stream are worth fact-checking, focusing on COVID-19 and politics in six languages: Arabic, Bulgarian, Dutch, English, Spanish, and Turkish. A total of 19 teams participated and most submissions managed to achieve sizable improvements over the baselines using Transformer-based models such as BERT and GPT-3. Across the four subtasks, approaches that targetted multiple languages (be it individually or in conjunction, in general obtained the best performance. We describe the dataset and the task setup, including the evaluation settings, and we give a brief overview of the participating systems. As usual in the CheckThat! lab, we release to the research community all datasets from the lab as well as the evaluation scripts, which should enable further research on finding relevant tweets that can help different stakeholders such as fact-checkers, journalists, and policymakers. © 2022 Copyright for this paper by its authors. | en_US |
dc.description.sponsorship | Hamad Bin Khalifa University, HBKU | en_US |
dc.description.sponsorship | Part of this work is made within the Tanbih mega-project, developed at the Qatar Computing Research Institute, HBKU, which aims to limit the impact of “fake news”, propaganda, and media bias by making users aware of what they are reading, thus promoting media literacy and critical thinking. | en_US |
dc.language.iso | en | en_US |
dc.publisher | CEUR-WS | en_US |
dc.relation.ispartof | CEUR Workshop Proceedings | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Check-Worthiness Estimation | en_US |
dc.subject | Computational Journalism | en_US |
dc.subject | COVID-19 | en_US |
dc.subject | Fact-Checking | en_US |
dc.subject | Social Media Verification | en_US |
dc.subject | Veracity | en_US |
dc.subject | Laboratories | en_US |
dc.subject | Social networking (online) | en_US |
dc.subject | Check-worthiness estimation | en_US |
dc.subject | Computational journalism | en_US |
dc.subject | Fact-checking | en_US |
dc.subject | Multiple languages | en_US |
dc.subject | Performance | en_US |
dc.subject | Social media | en_US |
dc.subject | Social medium verification | en_US |
dc.subject | Subtask | en_US |
dc.subject | Turkishs | en_US |
dc.subject | Veracity | en_US |
dc.subject | COVID-19 | en_US |
dc.title | Overview of the CLEF-2022 CheckThat! Lab Task 1 on Identifying Relevant Claims in Tweets | en_US |
dc.type | Conference Object | en_US |
dc.identifier.volume | 3180 | en_US |
dc.identifier.startpage | 368 | en_US |
dc.identifier.endpage | 392 | en_US |
dc.identifier.scopus | 2-s2.0-85136928741 | en_US |
dc.institutionauthor | Kutlu, Mücahid | - |
dc.authorscopusid | 15043153900 | - |
dc.authorscopusid | 26321398000 | - |
dc.authorscopusid | 55915092700 | - |
dc.authorscopusid | 56024506200 | - |
dc.authorscopusid | 57314168500 | - |
dc.authorscopusid | 35932126700 | - |
dc.authorscopusid | 35299304300 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | - | - |
dc.ozel | 2022v3_Edit | en_US |
item.cerifentitytype | Publications | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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