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Early detection of fake news on social media through propagation path classification with recurrent and convolutional networks
Yang Liu
,
Yi Fang Brook Wu
Informatics
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
608
Scopus citations
Overview
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Dive into the research topics of 'Early detection of fake news on social media through propagation path classification with recurrent and convolutional networks'. Together they form a unique fingerprint.
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Keyphrases
Early Detection
100%
Convolutional Networks
100%
Propagation Path
100%
Recurrent Network
100%
Fake News
100%
Path Classification
100%
Fake News on Social Media
100%
News Propagation
28%
General Public
14%
Social Media
14%
Machine Learning Algorithms
14%
Detection Method
14%
Academic Community
14%
Twitter
14%
News Story
14%
Local Variation
14%
Tuple
14%
Numerical Vector
14%
User Characteristics
14%
News Characteristics
14%
Global Variation
14%
Sina Weibo
14%
Multivariate Time Series
14%
Computer Science
Early Detection
100%
Social Media
100%
Convolutional Network
100%
Recurrent Network
100%
Propagation Path
100%
Experimental Result
25%
Academic Community
25%
Machine Learning Algorithm
25%
Multivariate Time Series
25%