Fake News Detection Using Ensemble Learning and Machine Learning Algorithms
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-90087-8_7
Reference30 articles.
1. Elyassami, S., & Kaddour, A. (2021). Implementation of an incremental deep learning model for survival prediction of cardiovascular patients. IAES International Journal of Artificial Intelligence. 10(1), 101–109. ISSN 2252–8938
2. Elyassami, S., Hamid, Y., & Habuza, T.: Road crashes analysis and prediction using gradient boosted and random forest trees. In 2020 6th IEEE Congress on Information Science and Technology (CiSt), Agadir—Essaouira, Morocco (pp. 520–525). https://doi.org/10.1109/CiSt49399.2021.9357298
3. Conroy, N. K., Rubin, V. L., & Chen, Y. (2015). Automatic deception detection: Methods for finding fake news. Proceedings of the Association for Information Science and Technology, 52(1), 1–4.
4. Pradhan, & Ajay, M. (2020). Fake news detection methods: Machine learning approach. International Journal for Research in Applied Science and Engineering Technology, 8(7), 971–975. https://doi.org/10.22214/ijraset.2020.29630
5. Maurice, V. (2018). Incorrect, fake, and false. journalists’ perceived online source credibility and verification behavior. Observatorio (OBS*) 12.1 (2018): n. pag. Web.
Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Detecting Fake Images Using Convolutional Neutral Networks - A Deep Learning Approach;International Journal of Innovative Science and Research Technology (IJISRT);2024-05-21
2. Disinformation detection using graph neural networks: a survey;Artificial Intelligence Review;2024-02-14
3. Detection of fake news: A comparative analysis using machine learning;AIP Conference Proceedings;2024
4. Highlighting bugs in software development codes using SDPET for enhancing security;Measurement: Sensors;2023-12
5. A Machine Learning Technique for Detection of Social Media Fake News;International Journal on Semantic Web and Information Systems;2023-07-20
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3