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Spam Detection in Social Media Networks: A Data Mining Approach

by Harshal S. Multani, Amrita Sinh Marod, Vinita Pillai, Vishal Gaware
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 9
Year of Publication: 2015
Authors: Harshal S. Multani, Amrita Sinh Marod, Vinita Pillai, Vishal Gaware
10.5120/20178-2385

Harshal S. Multani, Amrita Sinh Marod, Vinita Pillai, Vishal Gaware . Spam Detection in Social Media Networks: A Data Mining Approach. International Journal of Computer Applications. 115, 9 ( April 2015), 9-12. DOI=10.5120/20178-2385

@article{ 10.5120/20178-2385,
author = { Harshal S. Multani, Amrita Sinh Marod, Vinita Pillai, Vishal Gaware },
title = { Spam Detection in Social Media Networks: A Data Mining Approach },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 9 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number9/20178-2385/ },
doi = { 10.5120/20178-2385 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:54:20.880693+05:30
%A Harshal S. Multani
%A Amrita Sinh Marod
%A Vinita Pillai
%A Vishal Gaware
%T Spam Detection in Social Media Networks: A Data Mining Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 9
%P 9-12
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The ubiquitous use of social media has generated unparalleled amounts of social data. Data may be – text, numbers or facts that are computable by a computer. A particular data is absolutely useless until and unless converted into some useful information. It is necessary to analyze this massive amount of data and extracting useful information from it. There are more active internet users on social networks than search engines. Social media networks provide an easily accessible platform for users who wish to share information with others. Information can be spread across social networks quickly and effectively, hence have now become susceptible to different types of undesired and malicious spammer/hacker actions. Therefore, there is a pivotal need for security in social media and industry. In this demo, a scalable and online social media spam detection system for social network security using TF-IDF algorithm is proposed.

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Index Terms

Computer Science
Information Sciences

Keywords

Spam Social media networks Security TF-IDF.