RT-FEND: Spark-Based Real Time FakE News Detection-Reference-Cited by-同舟云学术

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RT-FEND: Spark-Based Real Time FakE News Detection

Published:2022-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Networking, Architecture and Storage (NAS)
language:
Short-container-title:

Author:

Zhang Chaowei¹,Gupta Ashish²,Sun Hui³,Li Yun¹,Qin Xiao⁴

Affiliation:

1. Yangzhou University,Department of Computer Science,Yangzhou,China

2. Auburn University,Department of Systems and Technology,Yangzhou,USA

3. School of Science and Technology Anhui University,Hefei,China

4. Auburn University,Department of Computer Science,Auburn,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9925246/9925275/09925512.pdf?arnumber=9925512

Reference29 articles.

1. The Wisdom of Twitter Crowds: Predicting Stock Market Reactions to FOMC Meetings via Twitter Feeds

2. Benchmarking big data architectures for social networks data processing using public cloud platforms

3. A smartphone-based wearable sensors for monitoring real-time physiological data;you;Computers & Electrical Engineering,2018

4. Media-Rich Fake News Detection: A Survey

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