Afcc: automatic fact-checkers’ consensus and credibility assessment for fake news detection
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41870-024-01956-1.pdf
Reference19 articles.
1. Aïmeur E, Hage H, Amri S (2018) The scourge of online deception in social networks. In: 2018 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 1266–1271. IEEE. https://doi.org/10.1109/CSCI46756.2018.00244
2. Aïmeur E, Amri S, Brassard G (2023) Fake news, disinformation and misinformation in social media: a review. Soc Netw Anal Min 13(1):30. https://doi.org/10.1007/s13278-023-01028-5
3. Thorne J, Vlachos A (2018) Automated fact checking: task formulations, methods and future directions. arXiv preprint arXiv:1806.07687
4. Allen J, Arechar AA, Pennycook G, Rand DG (2021) Scaling up fact-checking using the wisdom of crowds. Sci Adv 7(36):4393. https://doi.org/10.1126/sciadv.abf4393
5. Nyhan B, Porter E, Reifler J, Wood TJ (2020) Taking fact-checks literally but not seriously? The effects of journalistic fact-checking on factual beliefs and candidate favorability. Polit Behav 42(3):939–960. https://doi.org/10.1007/s11109-019-09528-x
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