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Machine learning and user social engagement based approaches for fake news/fake accounts detection in OSN

By:

Santhosh Kumar Uppada

Contributor(s):

[Dr. Sivaselvan]

Publication details: IIITDM Kancheepuram Computer Science August 2023Description: 217pSubject(s):

Online social network; yellow journalism; association rule based classifier; user engagement patterns; error level analysis; fusion models; clickbait; epidemic models; stacking generalization; basic reproduction number

DDC classification:

Dissertation note: Machine Learning Summary: Social network is a collection of social actors or firms that connect and share information. The utilization of online social networks as the primary source of information has increased, along with the availability of online social platforms that provide news from various sources.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Theses and Dissertations	IIITDM Kancheepuram Library Theses and Dissertation	Theses and Dissertation	004 SAN (Browse shelf(Opens below))	Available		TD00578

Total holds: 0

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Previous	004 (043) SHA On the development of novel high- performance packet classification architectures	004 ISU Domain adaptive models for multi class brain abnormality classification	004 MAN Data hiding methods for digital image security	004 SAN Machine learning and user social engagement based approaches for fake news/fake accounts detection in OSN	004.02:004.056.54 THA Implementation of Network Routing Algorithms & Detection Systems	004.021 KAN High Performance Packet Dropping Algorithm	004.031.6 SAI Analysis and Applications of Scan-PUF	Next

Machine Learning

Social network is a collection of social actors or firms that connect and share information. The utilization of online social networks as the primary source of information has increased, along with the availability of online social platforms that provide news from various sources.

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