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With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic.
RoBERTa: A robustly optimized BERT pretraining approach
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The likert scale revisited
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COVID-Twitter-BERT: A natural language processing model to analyse COVID-19 content on Twitter
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Classification aware neural topic model and its application on a new COVID-19 disinformation corpus
Xingyi Song, Johann Petrak, Ye Jiang, Iknoor Singh, Diana Maynard, and Kalina Bontcheva. 2020 · 2006
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Arkin Dharawat, Ismini Lourentzou, Alex Morales, and ChengXiang Zhai. 2020 · 2010
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Finding credible information sources in social networks based on content and social structure
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On the stratification of multi-label data
Konstantinos Sechidis, Grigorios Tsoumakas, and Ioannis Vlahavas. 2011 · 2011
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Detecting check-worthy factual claims in presidential debates
Naeemul Hassan, Chengkai Li, and Mark Tremayne. 2015 · 2015
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Social media usage
Andrew Perrin. 2015 · 2015
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XGBoost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin. 2016 · 2016
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BotOrNot: A system to evaluate social bots
Clayton Allen Davis, Onur Varol, Emilio Ferrara, Alessandro Flammini, and Filippo Menczer. 2016 · 2016
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SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours
Leon Derczynski, Kalina Bontcheva, Maria Liakata, Rob Procter, Geraldine Wong Sak Hoi, and Arkaitz Zubiaga. 2017 · 2017
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A context-aware approach for detecting worth-checking claims in political debates
Pepa Gencheva, Preslav Nakov, Lluís Màrquez, Alberto Barrón-Cedeño, and Ivan Koychev. 2017 · 2017
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Bag of tricks for efficient text classification
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2017 · 2017
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TATHYA: A multi-classifier system for detecting check-worthy statements in political debates
Ayush Patwari, Dan Goldwasser, and Saurabh Bagchi. 2017 · 2017
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Truth of varying shades: Analyzing language in fake news and political fact-checking
Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova, and Yejin Choi. 2017 · 2017
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“Liar, liar pants on fire”: A new benchmark dataset for fake news detection
William Yang Wang. 2017 · 2017
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Integrating stance detection and fact checking in a unified corpus
Ramy Baly, Mitra Mohtarami, James Glass, Lluís Màrquez, Alessandro Moschitti, and Preslav Nakov. 2018 · 2018
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Weaponized health communication: Twitter bots and Russian trolls amplify the vaccine debate
David A Broniatowski, Amelia M Jamison, SiHua Qi, Lulwah AlKulaib, Tao Chen, Adrian Benton, Sandra C Quinn, and Mark Dredze. 2018 · 2018
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ClaimRank: Detecting check-worthy claims in Arabic and English
Israa Jaradat, Pepa Gencheva, Alberto Barrón-Cedeño, Lluís Màrquez, and Preslav Nakov. 2018 · 2018
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Overview of the CLEF-2018 CheckThat! lab on automatic identification and verification of political claims
Preslav Nakov, Alberto Barrón-Cedeño, Tamer Elsayed, Reem Suwaileh, Lluís Màrquez, Wajdi Zaghouani, Pepa Atanasova, Spas Kyuchukov, and Giovanni Da San Martino. 2018 · 2018
Cited alongside, same era.
FEVER: a large-scale dataset for fact extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018 · 2018
Cited alongside, same era.
MultiFC: A real-world multi-domain dataset for evidence-based fact checking of claims
Isabelle Augenstein, Christina Lioma, Dongsheng Wang, Lucas Chaves Lima, Casper Hansen, Christian Hansen, and Jakob Grue Simonsen. 2019 · 2019
Cited alongside, same era.
Multi-task ordinal regression for jointly predicting the trustworthiness and the leading political ideology of news media
Ramy Baly, Georgi Karadzhov, Abdelrhman Saleh, James Glass, and Preslav Nakov. 2019 · 2019
Cited alongside, same era.
Proppy: A system to unmask propaganda in online news
Alberto Barrón-Cedeño, Giovanni Da San Martino, Israa Jaradat, and Preslav Nakov. 2019 · 2019
COVIDLies: Detecting COVID-19 misinformation on social media
Tamanna Hossain, Robert L. Logan IV, Arjuna Ugarte, Yoshitomo Matsubara, Sean Young, and Sameer Singh. 2020 · 2020
Closest in time.
Characterizing the propagation of situational information in social media during COVID-19 epidemic: A case study on Weibo
Lifang Li, Qingpeng Zhang, Xiao Wang, Jun Zhang, Tao Wang, Tian-Lu Gao, Wei Duan, Kelvin Kam-fai Tsoi, and Fei-Yue Wang. 2020 · 2020
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BERTweet: A pre-trained language model for English tweets
Dat Quoc Nguyen, Thanh Vu, and Anh Tuan Nguyen. 2020 · 2020
Closest in time.
COVID-19 infodemic: More retweets for science-based information on coronavirus than for false information
Cristina M Pulido, Beatriz Villarejo-Carballido, Gisela Redondo-Sama, and Aitor Gómez. 2020 · 2020
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GeoCoV19: A dataset of hundreds of millions of multilingual COVID-19 tweets with location information
Umair Qazi, Muhammad Imran, and Ferda Ofli. 2020 · 2020
Closest in time.
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Cited alongside, same era.
Proppy: Organizing the news based on their propagandistic content
Alberto Barrón-Cedeño, Israa Jaradat, Giovanni Da San Martino, and Preslav Nakov. 2019 · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
CheckThat! at CLEF 2019: Automatic identification and verification of claims
Tamer Elsayed, Preslav Nakov, Alberto Barrón-Cedeño, Maram Hasanain, Reem Suwaileh, Giovanni Da San Martino, and Pepa Atanasova. 2019 · 2019
Cited alongside, same era.
SemEval-2019 task 7: RumourEval, determining rumour veracity and support for rumours
Genevieve Gorrell, Ahmet Aker, Kalina Bontcheva, Leon Derczynski, Elena Kochkina, Maria Liakata, and Arkaitz Zubiaga. 2019 · 2019
Cited alongside, same era.
An “Infodemic”: Leveraging High-Volume Twitter Data to Understand Early Public Sentiment for the Coronavirus Disease 2019 Outbreak
Richard J Medford, Sameh N Saleh, Andrew Sumarsono, Trish M Perl, and Christoph U Lehmann. 2020 · 2019
Cited alongside, same era.
SemEval-2019 task 8: Fact checking in community question answering forums
Tsvetomila Mihaylova, Georgi Karadzhov, Pepa Atanasova, Ramy Baly, Mitra Mohtarami, and Preslav Nakov. 2019 · 2019
Cited alongside, same era.
ClaimsKG: A knowledge graph of fact-checked claims
Andon Tchechmedjiev, Pavlos Fafalios, Katarina Boland, Malo Gasquet, Matthäus Zloch, Benjamin Zapilko, Stefan Dietze, and Konstantin Todorov. 2019 · 2019
Cited alongside, same era.
Can the crowd identify misinformation objectively? The effects of judgment scale and assessor’s background
Kevin Roitero, Michael Soprano, Shaoyang Fan, Damiano Spina, Stefano Mizzaro, and Gianluca Demartini. 2020 · 2020
Closest in time.
Overview of CheckThat! 2020 English: Automatic identification and verification of claims in social media
Shaden Shaar, Alex Nikolov, Nikolay Babulkov, Firoj Alam, Alberto Barrón-Cedeño, Tamer Elsayed, Maram Hasanain, Reem Suwaileh, Fatima Haouari, Giovanni Da San Martino, and Preslav Nakov. 2020 · 2020
Closest in time.
FakeCovid – a multilingual cross-domain fact check news dataset for COVID-19
Gautam Kishore Shahi and Durgesh Nandini. 2020 · 2020
Closest in time.
Detecting East Asian prejudice on social media
Bertie Vidgen, Scott Hale, Ella Guest, Helen Margetts, David Broniatowski, Zeerak Waseem, Austin Botelho, Matthew Hall, and Rebekah Tromble. 2020 · 2020
Closest in time.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Closest in time.
ReCOVery: A multimodal repository for COVID-19 news credibility research
Xinyi Zhou, Apurva Mulay, Emilio Ferrara, and Reza Zafarani. 2020 · 2020
Closest in time.
Mega-COV: A billion-scale dataset of 100+ languages for COVID-19
Muhammad Abdul-Mageed, AbdelRahim Elmadany, El Moatez Billah Nagoudi, Dinesh Pabbi, Kunal Verma, and Rannie Lin. 2021 · 2021
Closest in time.
AraStance: A multi-country and multi-domain dataset of Arabic stance detection for fact checking
Tariq Alhindi, Amal Alabdulkarim, Ali Alshehri, Muhammad Abdul-Mageed, and Preslav Nakov. 2021 · 2021
Closest in time.
A large-scale COVID-19 Twitter chatter dataset for open scientific research – an international collaboration
Juan M. Banda, Ramya Tekumalla, Guanyu Wang, Jingyuan Yu, Tuo Liu, Yuning Ding, Ekaterina Artemova, Elena Tutubalina, and Gerardo Chowell. 2021 · 2021
Closest in time.
SemEval-2021 task 6: Detection of persuasion techniques in texts and images
Dimitar Dimitrov, Bishr Bin Ali, Shaden Shaar, Firoj Alam, Fabrizio Silvestri, Hamed Firooz, Preslav Nakov, and Giovanni Da San Martino. 2021b · 2021
Closest in time.
ArCOV-19: The first Arabic COVID-19 Twitter dataset with propagation networks
Fatima Haouari, Maram Hasanain, Reem Suwaileh, and Tamer Elsayed. 2021 · 2021
Closest in time.
Toward automated factchecking: Developing an annotation schema and benchmark for consistent automated claim detection
Lev Konstantinovskiy, Oliver Price, Mevan Babakar, and Arkaitz Zubiaga. 2021 · 2021
Closest in time.
Overview of the CLEF-2021 CheckThat! lab on detecting check-worthy claims, previously fact-checked claims, and fake news
Preslav Nakov, Giovanni Da San Martino, Tamer Elsayed, Alberto Barrón-Cedeño, Rubén Míguez, Shaden Shaar, Firoj Alam, Fatima Haouari, Maram Hasanain, Watheq Mansour, Bayan Hamdan, Zien Sheikh Ali, Nikolay Babulkov, Alex Nikolov, Gautam Kishore Shahi, Julia Maria Struß, Thomas Mandl, Mucahid Kutlu, and Yavuz Selim Kartal. 2021c · 2021
Closest in time.
Findings of the NLP4IF-2021 shared tasks on fighting the COVID-19 infodemic and censorship detection
Shaden Shaar, Firoj Alam, Giovanni Da San Martino, Alex Nikolov, Wajdi Zaghouani, Preslav Nakov, and Anna Feldman. 2021a · 2021
Closest in time.
Overview of the CLEF-2021 CheckThat! lab task 2 on detecting previously fact-checked claims in tweets and political debates
Shaden Shaar, Fatima Haouari, Watheq Mansour, Maram Hasanain, Nikolay Babulkov, Firoj Alam, Giovanni Da San Martino, Tamer Elsayed, and Preslav Nakov. 2021b · 2021
Closest in time.
Overview of the CLEF-2021 CheckThat! lab task 1 on check-worthiness estimation in tweets and political debates
Shaden Shaar, Maram Hasanain, Bayan Hamdan, Zien Sheikh Ali, Fatima Haouari, Alex Nikolov, Mucahid Kutlu, Yavuz Selim Kartal, Firoj Alam, Giovanni Da San Martino, Alberto Barrón-Cedeño, Rubén Míguez, Javier Beltrán, Tamer Elsayed, and Preslav Nakov. 2021c · 2021
Closest in time.
Interpretable propaganda detection in news articles
Seunghak Yu, Giovanni Da San Martino, Mitra Mohtarami, James Glass, and Preslav Nakov. 2021 · 2021
Closest in time.