Optimized Convolution Neural Network Based Fake News Detection Using Sentiment Analysis-Reference-Cited by-同舟云学术

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Optimized Convolution Neural Network Based Fake News Detection Using Sentiment Analysis

Published:2024-04-26 Issue: Volume: Page:01-04
ISSN:
Container-title:2024 Third International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)
language:
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Author:

Vadakkethil Somanathan Pillai Sanjaikanth E¹,Rajashekaran Karthik²,Archana Reddy R.³,Kumar Pareek Piyush⁴,Sontakke Dipti⁵

Affiliation:

1. School of Electrical Engineering and Computer Science, University of North Dakota,Grand Forks,USA

2. New York University,Department of Computer Science,New York,NY,USA

3. School of Computer Science and Engineering, SR University,Warangal,Telangana,India

4. Nitte Meenakshi Institute of Technology,Department of AIML and IPR Cell,Bengaluru,India

5. Capgemini Inc,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10548017/10548035/10549302.pdf?arnumber=10549302

Reference15 articles.

1. Fake news detection in social media based on sentiment analysis using classifier techniques

2. A combined deep learning model based on the ideal distance weighting method for fake news detection

3. Fake News Detection Model on Social Media by Leveraging Sentiment Analysis of News Content and Emotion Analysis of Users’ Comments

4. AENeT: an attention-enabled neural architecture for fake news detection using contextual features

5. Fake News Classification Using a Fuzzy Convolutional Recurrent Neural Network

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