Call for Papers:Vol.11 Issue.3

Submission
Last date		 28-Jun-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-3. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Machine learning methods for Fake news detection - Literature Survey
PaperId: :  17543
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 8 Issue 3 2022
DUI:    16.0415/IJARIIE-17543
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Anisha SomanIES College of Engineering, Thrissur, Kerala, India
Hrudya K P IES College of Engineering, Thrissur, Kerala, India
Dr G KIRUTHIGA IES College of Engineering, Thrissur, Kerala, India

Abstract

Computer Engineering
Social media, Fake News, Algorithms, Digital tools, Machine Learning
In the modern time the internet is ubiquitous, everyone relies on various online resources for news. Along with the increase in the use of social media platforms like Facebook, Twitter, etc. 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. With the widespread dissemination of information via digital media platforms, it is of utmost importance for individuals and societies to be able to judge the credibility of it. Fake news is not a recent concept, but it is a commonly occurring phenomenon in current times. The consequence of fake news can range from being merely annoying to influencing and misleading societies or even nations. A variety of approaches exist to identify fake news. By conducting a systematic literature review, we identify the main approaches currently available to identify fake news and how these approaches can be applied in different situations. Some approaches are illustrated with a relevant example as well as the challenges and the appropriate context in which the specific approach can be used. 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.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Anisha Soman, Hrudya K P , and Dr G KIRUTHIGA . "Machine learning methods for Fake news detection - Literature Survey" International Journal Of Advance Research And Innovative Ideas In Education Volume 8 Issue 3 2022 Page 5134-5138
MLA Anisha Soman, Hrudya K P , and Dr G KIRUTHIGA . "Machine learning methods for Fake news detection - Literature Survey." International Journal Of Advance Research And Innovative Ideas In Education 8.3(2022) : 5134-5138.
APA Anisha Soman, Hrudya K P , & Dr G KIRUTHIGA . (2022). Machine learning methods for Fake news detection - Literature Survey. International Journal Of Advance Research And Innovative Ideas In Education, 8(3), 5134-5138.
Chicago Anisha Soman, Hrudya K P , and Dr G KIRUTHIGA . "Machine learning methods for Fake news detection - Literature Survey." International Journal Of Advance Research And Innovative Ideas In Education 8, no. 3 (2022) : 5134-5138.
Oxford Anisha Soman, Hrudya K P , and Dr G KIRUTHIGA . 'Machine learning methods for Fake news detection - Literature Survey', International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, 2022, p. 5134-5138. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Machine_learning_methods_for_Fake_news_detection___Literature_Survey_ijariie17543.pdf (Accessed : 26 March 2024).
Harvard Anisha Soman, Hrudya K P , and Dr G KIRUTHIGA . (2022) 'Machine learning methods for Fake news detection - Literature Survey', International Journal Of Advance Research And Innovative Ideas In Education, 8(3), pp. 5134-5138IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Machine_learning_methods_for_Fake_news_detection___Literature_Survey_ijariie17543.pdf (Accessed : 26 March 2024)
IEEE Anisha Soman, Hrudya K P , and Dr G KIRUTHIGA , "Machine learning methods for Fake news detection - Literature Survey," International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, pp. 5134-5138, May-Jun 2022. [Online]. Available: https://ijariie.com/AdminUploadPdf/Machine_learning_methods_for_Fake_news_detection___Literature_Survey_ijariie17543.pdf [Accessed : 26 March 2024].
Turabian Anisha Soman, Hrudya K P , and Dr G KIRUTHIGA . "Machine learning methods for Fake news detection - Literature Survey." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 8 number 3 (26 March 2024).
Vancouver Anisha Soman, Hrudya K P , and Dr G KIRUTHIGA . Machine learning methods for Fake news detection - Literature Survey. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2022 [Cited : 26 March 2024]; 8(3) : 5134-5138. Available from: https://ijariie.com/AdminUploadPdf/Machine_learning_methods_for_Fake_news_detection___Literature_Survey_ijariie17543.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads


Last download on 3/26/2024 6:23:34 AM

Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
PREDICTING GENETIC VARIANTS PATHOGENECITYComputer EngineeringSyed Arbeena Kausar Download
ANDROID MALWARE DETECTION USING MACHINE LEARNING TECHNIQUESCOMPUTER SCIENCE AND ENGINEERINGS. Saiful Islam Download
IMPROVING HEALTHCARE PREDICTION OF DIABETIC PATIENTS USING KNN IMPUTED FEATURES AND TRI-ENSEMBLE MODELCOMPUTER SCIENCE AND ENGINEERINGS. Mahammad Arif Download
MONEY LAUNDERING DETECTION USING MACHINE LEARNING METHODSCOMPUTER SCIENCE AND ENGINEERINGY B. Shashank Raj Download
LEVERAGING SPATIOTEMPORAL PATTERNS FOR CYBER ATTACK DETECTION IN DISTRIBUTION SYSTEMCOMPUTER SCIENCE AND ENGINEERINGV. Kumar Download
Real-Time Heart Disease Prediction Using Machine LearningCOMPUTER SCIENCE AND ENGINEERINGP. Sri Pavan Hari Charan Download
HAND AND FACE LANDMARKS DETECTION USING MEDIA PIPE AND AICOMPUTER SCIENCE AND ENGINEERINGK. V. Bharath Kumar Download
VEHICLES SPEED DETECTION SYSTEM USING OPENCVCOMPUTER SCIENCE AND ENGINEERINGS. Santosh Download
SUSPICIOUS HUMAN ACTIVITY RECOGNITION FROM SURVEILLANCE VIDEOS USING DEEP LEARNINGCOMPUTER SCIENCE AND ENGINEERINGM. Lakshmi kanth Download
DETECTION OF THYROID DISORDERS USING MACHINE LEARNING APPOARCHCOMPUTER SCIENCE AND ENGINEERINGP. Shamiulla Download
Events Recommendation SystemComputer Science and EngineeringDharsana S Download
Online Attendance Using Web ApplicationComputer EngineeringMrs. P. Saranya Download
Automated Pneumonia Detection Using ResNet50 Deep Learning ModelDepartment of Computer Science & Engineering, D.Y.Patil Technical Campus, Shivaji University, KolhapurSohan Sanjay Kamalakar Download
MULTI-DISEASE DETECTION USING MACHINE LEARNINGComputer EngineeringNamithadevi N N Download
NETWORK TRAFFIC ANALYSIS WITH BIG DATA AND DEEP LEARNING TECHNIQUESCOMPUTER SCIENCE AND ENGINEERINGD VYSHNAVI Download
12