short-paper

FACTCK.BR: a new dataset to study fake news

Authors:

João Moreno,

Graça BressanAuthors Info & Claims

WebMedia '19: Proceedings of the 25th Brazillian Symposium on Multimedia and the Web

Pages 525 - 527

https://doi.org/10.1145/3323503.3361698

Published: 29 October 2019 Publication History

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Abstract

Machine learning algorithms can be used to combat fake news propagation. For the news classification, labeled datasets are required, however, among the existing datasets, few separate verified false from skewed ones with a good variety of sources. This work presents FACTCK.BR, a new dataset to study Fake News in Portuguese, presenting a supposedly false News along with their respective fact check and classification. The data is collected from the ClaimReview, a structured data schema used by fact check agencies to share their results in search engines, enabling data collect in real time.

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Lucas Graves. 2018. Understanding the promise and limits of automated fact-checking. Factsheet 2 (2018), 2018--02.

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Naeemul Hassan, Bill Adair, James T Hamilton, Chengkai Li, Mark Tremayne, Jun Yang, and Cong Yu. 2015. The quest to automate fact-checking. In Proceedings of the 2015 Computation+ Journalism Symposium.

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Naeemul Hassan, Gensheng Zhang, Fatma Arslan, Josue Caraballo, Damian Jimenez, Siddhant Gawsane, Shohedul Hasan, Minumol Joseph, Aaditya Kulkarni, Anil Kumar Nayak, et al. 2017. Claimbuster: The first-ever end-to-end fact-checking system. Proceedings of the VLDB Endowment 10, 12 (2017), 1945--1948.

Digital Library

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Rafael A. Monteiro, Roney L. S. Santos, Thiago A. S. Pardo, Tiago A. de Almeida, Evandro E. S. Ruiz, and Oto A. Vale. 2018. Contributions to the Study of Fake News in Portuguese: New Corpus and Automatic Detection Results. In Computational Processing of the Portuguese Language. Springer International Publishing, 324--334.

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Marcio Moretto Ribeiro Pablo Ortellado. 2018. Polarização e desinformação online no Brasil (44 ed.).

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Victoria L Rubin, Yimin Chen, and Niall J Conroy. 2015. Deception detection for news: three types of fakes. In Proceedings of the 78th ASIS&T Annual Meeting: Information Science with Impact: Research in and for the Community. American Society for Information Science, 83.

Crossref

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William Yang Wang. 2017. "liar, liar pants on fire": A new benchmark dataset for fake news detection. arXiv preprint arXiv:1705.00648 (2017).

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Cited By

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Puska APereira R(2023)Exploring Digital Misinformation as a Sociotechnical Phenomenon: Insights from a Small-scale StudyProceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems10.1145/3638067.3638098(1-12)Online publication date: 16-Oct-2023
https://dl.acm.org/doi/10.1145/3638067.3638098
Durier da Silva FCristina Bicharra Garcia AMatsui Siqueira S(2022)A Systematic Literature Mapping on Profile Trustworthiness in Fake News Spread2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD54268.2022.9776232(275-279)Online publication date: 4-May-2022
https://doi.org/10.1109/CSCWD54268.2022.9776232
Garcia GAfonso LPapa J(2022)FakeRecogna: A New Brazilian Corpus for Fake News DetectionComputational Processing of the Portuguese Language10.1007/978-3-030-98305-5_6(57-67)Online publication date: 16-Mar-2022
https://doi.org/10.1007/978-3-030-98305-5_6
Show More Cited By

Index Terms

FACTCK.BR: a new dataset to study fake news
1. Applied computing
  1. Document management and text processing
    1. Document searching

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Information & Contributors

Information

Published In

WebMedia '19: Proceedings of the 25th Brazillian Symposium on Multimedia and the Web

October 2019

537 pages

ISBN:9781450367639

DOI:10.1145/3323503

General Chairs:
Joel dos Santos
CEFET/RJ
,
Débora Christina Muchaluat Saade
UFF
,
Maria da Graça C. Pimentel
University of Sao Paulo, Brazil
,
Alessandra Alaniz Macedo
University of Sao Paulo, Brazil

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 October 2019

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WebMedia '19

WebMedia '19: Brazilian Symposium on Multimedia and the Web

October 29 - November 1, 2019

Rio de Janeiro, Brazil

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Overall Acceptance Rate 270 of 873 submissions, 31%

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Cited By

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Puska APereira R(2023)Exploring Digital Misinformation as a Sociotechnical Phenomenon: Insights from a Small-scale StudyProceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems10.1145/3638067.3638098(1-12)Online publication date: 16-Oct-2023
https://dl.acm.org/doi/10.1145/3638067.3638098
Durier da Silva FCristina Bicharra Garcia AMatsui Siqueira S(2022)A Systematic Literature Mapping on Profile Trustworthiness in Fake News Spread2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD54268.2022.9776232(275-279)Online publication date: 4-May-2022
https://doi.org/10.1109/CSCWD54268.2022.9776232
Garcia GAfonso LPapa J(2022)FakeRecogna: A New Brazilian Corpus for Fake News DetectionComputational Processing of the Portuguese Language10.1007/978-3-030-98305-5_6(57-67)Online publication date: 16-Mar-2022
https://doi.org/10.1007/978-3-030-98305-5_6
Spalenza Mde Oliveira ELusquino-Filho LLima PFrança F(2021)Using NER + ML to Automatically Detect Fake NewsIntelligent Systems Design and Applications10.1007/978-3-030-71187-0_109(1176-1187)Online publication date: 3-Jun-2021
https://doi.org/10.1007/978-3-030-71187-0_109
Horák ABaisa VHerman O(2021)Technological Approaches to Detecting Online Disinformation and ManipulationChallenging Online Propaganda and Disinformation in the 21st Century10.1007/978-3-030-58624-9_5(139-166)Online publication date: 10-Mar-2021
https://doi.org/10.1007/978-3-030-58624-9_5
de Souza Mda Silva FFreire PGoldschmidt Rde Salles Soares Neto C(2020)A Linguistic-Based Method that Combines Polarity, Emotion and Grammatical Characteristics to Detect Fake News in PortugueseProceedings of the Brazilian Symposium on Multimedia and the Web10.1145/3428658.3430975(217-224)Online publication date: 30-Nov-2020
https://dl.acm.org/doi/10.1145/3428658.3430975
da Silva FFreire Pde Souza Mde A. B. Plenamente GGoldschmidt Rde Salles Soares Neto C(2020)FakeNewsSetGenProceedings of the Brazilian Symposium on Multimedia and the Web10.1145/3428658.3430965(241-248)Online publication date: 30-Nov-2020
https://dl.acm.org/doi/10.1145/3428658.3430965
Zubiaga AJiang A(2020)Early Detection of Social Media Hoaxes at ScaleACM Transactions on the Web10.1145/340719414:4(1-23)Online publication date: 18-Aug-2020
https://dl.acm.org/doi/10.1145/3407194

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