Detecting Fake News using Machine Learning: A Systematic Literature Review

Author:

Et al. Alim Al Ayub Ahmed

Abstract

Internet is one of the important inventions and a large number of persons are its users. These persons use this for different purposes. There are different social media platforms that are accessible to these users. Any user can make a post or spread the news through these online platforms. These platforms do not verify the users or their posts. So some of the users try to spread fake news through these platforms. These fake news can be a propaganda against an individual, society, organization or political party. A human being is unable to detect all these fake news. So there is a need for machine learning classifiers that can detect these fake news automatically. Use of machine learning classifiers for detecting the fake news is described in this systematic literature review.

Publisher

Auricle Technologies, Pvt., Ltd.

Subject

General Psychology,Developmental and Educational Psychology,Education

Cited by 20 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. Intelligent Framework to Detection of Fake News Using Deep Learning Approach;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28

2. Modelling a dense hybrid network model for fake review analysis using learning approaches;Soft Computing;2024-01-29

3. Enhancing Machine-Generated Text Detection: Adversarial Fine-Tuning of Pre-Trained Language Models;IEEE Access;2024

4. Combining human intelligence and machine learning for fact-checking: Towards a hybrid human-in-the-loop framework;Intelligenza Artificiale;2023-12-20

5. Fake News Detection Using Machine Learning Algorithm;2023 International Conference on Communication, Security and Artificial Intelligence (ICCSAI);2023-11-23

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