Automated Fact-Checking for Assisting Human Fact-Checkers
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Paolo Papotti | Firoj Alam | Giovanni Da San Martino | Maram Hasanain | David Corney | Shaden Shaar | Preslav Nakov | Tamer Elsayed | Alberto Barr'on-Cedeno | Paolo Papotti | D. Corney | Firoj Alam | Preslav Nakov | Tamer Elsayed | Shaden Shaar | Maram Hasanain | A. Barr'on-Cedeno
[1] Emily B. Fox,et al. A Bayesian Approach for Predicting the Popularity of Tweets , 2013, ArXiv.
[2] Smaranda Muresan,et al. Where is Your Evidence: Improving Fact-checking by Justification Modeling , 2018 .
[3] Preslav Nakov,et al. A Survey on Computational Propaganda Detection , 2020, IJCAI.
[4] Zita Marinho,et al. Automated Fact Checking in the News Room , 2019, WWW.
[5] Bo Zhao,et al. A Survey on Truth Discovery , 2015, SKDD.
[6] Preslav Nakov,et al. Fact-Checking Meets Fauxtography: Verifying Claims About Images , 2019, EMNLP.
[7] Eunsol Choi,et al. Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking , 2017, EMNLP.
[8] Jisun An,et al. A Survey on Predicting the Factuality and the Bias of News Media , 2021, ArXiv.
[9] Firoj Alam,et al. The Role of Context in Detecting Previously Fact-Checked Claims , 2021, ArXiv.
[10] Iryna Gurevych,et al. UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification , 2018, FEVER@EMNLP.
[11] Wenhu Chen,et al. TabFact: A Large-scale Dataset for Table-based Fact Verification , 2019, ICLR.
[12] L. Christophorou. Science , 2018, Emerging Dynamics: Science, Energy, Society and Values.
[13] Andreas Vlachos,et al. The Fact Extraction and VERification (FEVER) Shared Task , 2018, ArXiv.
[14] Firoj Alam,et al. A Survey on Multimodal Disinformation Detection , 2021, ArXiv.
[15] Alberto Barrón-Cedeño,et al. The CLEF-2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News , 2021, ECIR.
[16] Andrew G. Glen,et al. APPL , 2001 .
[17] Haonan Chen,et al. Combining Fact Extraction and Verification with Neural Semantic Matching Networks , 2018, AAAI.
[18] Isabelle Augenstein,et al. Fact Check-Worthiness Detection as Positive Unlabelled Learning , 2020, EMNLP.
[19] Jimmy J. Lin,et al. Cross-Domain Modeling of Sentence-Level Evidence for Document Retrieval , 2019, EMNLP.
[20] Preslav Nakov,et al. It Takes Nine to Smell a Rat: Neural Multi-Task Learning for Check-Worthiness Prediction , 2019, RANLP.
[21] Maram Hasanain,et al. bigIR at CheckThat! 2020: Multilingual BERT for Ranking Arabic Tweets by Check-worthiness , 2020, CLEF.
[22] Preslav Nakov,et al. Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models , 2020, CLEF.
[23] Preslav Nakov,et al. A Context-Aware Approach for Detecting Worth-Checking Claims in Political Debates , 2017, RANLP.
[24] Ben Adler,et al. Real-time Claim Detection from News Articles and Retrieval of Semantically-Similar Factchecks , 2019, NewsIR@SIGIR.
[25] Chengkai Li,et al. Toward Automated Fact-Checking: Detecting Check-worthy Factual Claims by ClaimBuster , 2017, KDD.
[26] Henning Wachsmuth,et al. Extractive Snippet Generation for Arguments , 2020, SIGIR.
[27] Gerhard Weikum,et al. Credibility Assessment of Textual Claims on the Web , 2016, CIKM.
[28] Gerhard Weikum,et al. Tracy: Tracing Facts over Knowledge Graphs and Text , 2019, WWW.
[29] Neema Kotonya,et al. Explainable Automated Fact-Checking: A Survey , 2020, COLING.
[30] Paolo Papotti,et al. Scrutinizer , 2020, Proc. VLDB Endow..
[31] Kyumin Lee,et al. The Rise of Guardians: Fact-checking URL Recommendation to Combat Fake News , 2018, SIGIR.
[32] J. Meigs,et al. WHO Technical Report , 1954, The Yale Journal of Biology and Medicine.
[33] Jacob Daniel Devasier,et al. Gradient-Based Adversarial Training on Transformer Networks for Detecting Check-Worthy Factual Claims , 2020, ArXiv.
[34] Paolo Papotti,et al. Explainable Fact Checking with Probabilistic Answer Set Programming , 2019, TTO.
[35] Chengkai Li,et al. Detecting Check-worthy Factual Claims in Presidential Debates , 2015, CIKM.
[36] Editors , 1986, Brain Research Bulletin.
[37] Barbara Poblete,et al. Information credibility on twitter , 2011, WWW.
[38] Preslav Nakov,et al. Overview of CheckThat 2020: Automatic Identification and Verification of Claims in Social Media , 2020, CLEF.
[39] Damian Jimenez,et al. ClaimPortal: Integrated Monitoring, Searching, Checking, and Analytics of Factual Claims on Twitter , 2019, ACL.
[40] Preslav Nakov,et al. Overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. Task 1: Check-Worthiness , 2018, CLEF.
[41] Rafael Vieira,et al. Can Machines Learn to Detect Fake News? A Survey Focused on Social Media , 2019, HICSS.
[42] Preslav Nakov,et al. ClaimRank: Detecting Check-Worthy Claims in Arabic and English , 2018, NAACL.
[43] Mucahid Kutlu,et al. Too Many Claims to Fact-Check: Prioritizing Political Claims Based on Check-Worthiness , 2020, CIKM.
[44] Preslav Nakov,et al. CheckThat! at CLEF 2019: Automatic Identification and Verification of Claims , 2019, ECIR.
[45] Kyumin Lee,et al. Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News , 2020, EMNLP.
[46] Andreas Vlachos,et al. Automated Fact Checking: Task Formulations, Methods and Future Directions , 2018, COLING.
[47] Fabio Petroni,et al. Generating Fact Checking Briefs , 2020, EMNLP.
[48] Preslav Nakov,et al. That is a Known Lie: Detecting Previously Fact-Checked Claims , 2020, ACL.
[49] Arkaitz Zubiaga,et al. Towards Automated Factchecking: Developing an Annotation Schema and Benchmark for Consistent Automated Claim Detection , 2018, ArXiv.
[50] Emily M. Bender,et al. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 , 2021, FAccT.
[51] Madian Khabsa,et al. Towards Few-shot Fact-Checking via Perplexity , 2021, NAACL.
[52] Preslav Nakov,et al. CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Media , 2020, ECIR.
[53] Vinay Setty,et al. BRENDA: Browser Extension for Fake News Detection , 2020, SIGIR.
[54] Paul Rodrigues,et al. Accenture at CheckThat! 2020: If you say so: Post-hoc fact-checking of Claims using Transformer-based Models , 2020, CLEF.
[55] Andreas Vlachos,et al. Fact Checking: Task definition and dataset construction , 2014, LTCSS@ACL.
[56] Preslav Nakov,et al. FANG: Leveraging Social Context for Fake News Detection Using Graph Representation , 2020, CIKM.
[57] LiakataMaria,et al. Detection and Resolution of Rumours in Social Media , 2018 .
[58] Christian Hansen,et al. MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims , 2019, EMNLP.
[59] Christopher Malon,et al. Team Papelo: Transformer Networks at FEVER , 2019, ArXiv.
[60] Xianzhi Wang,et al. Deep learning for misinformation detection on online social networks: a survey and new perspectives , 2020, Social Network Analysis and Mining.
[61] Sinan Aral,et al. The spread of true and false news online , 2018, Science.
[62] Suhang Wang,et al. Fake News Detection on Social Media: A Data Mining Perspective , 2017, SKDD.