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A Review Article on Detection of Fake Profile on Social-Media

Authors: Shamim Ahmad; Dr. Manish Madhava Tripathi;

A Review Article on Detection of Fake Profile on Social-Media

Abstract

Nowadays, practically everyone, from a youngster to an adult, spends more time on online social media platforms, connecting with and exchanging information with individuals all over the world. The social network is becoming a popular means to communicate with people who live in different parts of the world. Because of the tremendous interconnectedness and information sharing enabled by the internet, social media platforms. This highlights the importance of establishing a system capable of detecting fake profiles on social media networks. There has been a lot of study done in this area utilising machine learning algorithms to identify fake profile, duplicate, spam, and bot accounts, and most of the fake profile accounts were effectively recognised using machine learning algorithms. This study discusses fake profile detection on social networks using machine learning.

Related Organizations
Keywords

Fake Profile, Fake Identities, Security Issues, Social Network Analysis, Machine Learning

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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