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AI education matters: building a fake news detector

Published: 06 December 2019 Publication History

Abstract

Fake news is a salient societal issue, the subject of much recent academic research, and, as of 2019, a ubiquitous catchphrase.

References

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Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211--36.
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Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., & Lazer, D. (2019). Fake news on twitter during the 2016 us presidential election. Science, 363(6425), 374--378.
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Lazer, D. M., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., ... others (2018). The science of fake news. Science, 359(6380), 1094--1096.
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Mansky, J. (2018). The age-old problem of "fake news". Smithsonian Magazine. https://www.smithsonianmag.com/history/age-old-problem-fake-news-180968945/.
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Neller, T. W., Sooriamurthi, R., Guerzhoy, M., Zhang, L., Talaga, P., Archibald, C., ... others (2019). Model AI Assignments 2019. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 9751--9753).
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Nelson, J. L., & Taneja, H. (2018). The small, disloyal fake news audience: The role of audience availability in fake news consumption. New Media & Society, 20(10), 3720--3737.
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Pérez-Rosas, V., Kleinberg, B., Lefevre, A., & Mihalcea, R. (2018). Automatic detection of fake news. In Proceedings of the 27th International Conference on Computational Linguistics (pp. 3391--3401).
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Shu, K., Sliva, A., Wang, S., Tang, J., & Liu, H. (2017). Fake news detection on social media: A data mining perspective. SIGKDD Explorations Newsletter, 19(1), 22--36.
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Wang, W. Y. (2017). "Liar, liar pants on fire": A new benchmark dataset for fake news detection. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics.

Cited By

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  • (2024)AI in Computing Education from Research to PracticeProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 210.1145/3626253.3631657(1521-1522)Online publication date: 14-Mar-2024
  • (2020)A computationally intelligent agent for detecting fake news using generative adversarial networksHybrid Computational Intelligence10.1016/B978-0-12-818699-2.00004-4(69-96)Online publication date: 2020

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Published In

cover image AI Matters
AI Matters  Volume 5, Issue 3
September 2019
82 pages
EISSN:2372-3483
DOI:10.1145/3362077
Issue’s Table of Contents
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 December 2019
Published in SIGAI-AIMATTERS Volume 5, Issue 3

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Cited By

View all
  • (2024)AI in Computing Education from Research to PracticeProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 210.1145/3626253.3631657(1521-1522)Online publication date: 14-Mar-2024
  • (2020)A computationally intelligent agent for detecting fake news using generative adversarial networksHybrid Computational Intelligence10.1016/B978-0-12-818699-2.00004-4(69-96)Online publication date: 2020

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