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Reseach Article

Detection of Spam Messages in Social Networks based on SVM

by Sumaiya Pathan, R. H. Goudar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 10
Year of Publication: 2016
Authors: Sumaiya Pathan, R. H. Goudar

Sumaiya Pathan, R. H. Goudar . Detection of Spam Messages in Social Networks based on SVM. International Journal of Computer Applications. 145, 10 ( Jul 2016), 34-38. DOI=10.5120/ijca2016910793

@article{ 10.5120/ijca2016910793,
author = { Sumaiya Pathan, R. H. Goudar },
title = { Detection of Spam Messages in Social Networks based on SVM },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 10 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2016910793 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:48:27.807666+05:30
%A Sumaiya Pathan
%A R. H. Goudar
%T Detection of Spam Messages in Social Networks based on SVM
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 10
%P 34-38
%D 2016
%I Foundation of Computer Science (FCS), NY, USA

Social networks are platforms through which people communicate and share information. Some users commonly known as spammers are misusing these platforms for spreading unsolicited messages commonly known as spam messages. Due to the advancement of internet, it is very difficult to detect spam messages and fake profiles. This research article presents the use of a machine learning algorithm such SVM (Support Vector Machine), which is based on statistical learning methods to detect spam in social networks. This paper also evaluates the classification efficiency of Non Linear SVM using RBS (Radial Basis Function) Kernel.

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Index Terms

Computer Science
Information Sciences


Spam SVM RBS Kernel Machine Learning.