Supervised Machine Learning Approaches to Identify the False and True News from Social Media Data-Reference-Cited by-同舟云学术

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Supervised Machine Learning Approaches to Identify the False and True News from Social Media Data

Published:2024-02-23 Issue: Volume:4 Page:15-20
ISSN:
Container-title:2024 International Conference on Social and Sustainable Innovations in Technology and Engineering (SASI-ITE)
language:
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Author:

Sadik Md Rezwane¹,Rana Md Masum²,Akter Lima³,Islam Rafiul⁴,Rahman Md. Hasanur⁴,Rahman Md. Musfiqur⁴

Affiliation:

1. University of South Dakota,Department of Economics & Decision Sciences,Vermillion,SD,United States

2. University of South Dakota,Department of Computer Science,Vermillion,SD,United States

3. Atish Dipankar University of Science & Technology,Department of Computer Science and Engineering,Dhaka,Bangladesh

4. Daffodil International University,Department of Computer Science and Engineering,Dhaka,Bangladesh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10606964/10606945/10607126.pdf?arnumber=10607126

Reference34 articles.

1. Immunization strategies for false information spreading on signed social networks

2. A Proposed Bi-LSTM Method to Fake News Detection

3. Fake News Detection

4. Review Analysis of Ride-Sharing Applications Using Machine Learning Approaches

5. With Facebook, Blogs, and Fake News, Teens Reject Journalistic “Objectivity”

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