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Reseach Article

Scam-Alert: Characterizing Work from Home Scams on Social Networks

by Shaifali Gupta, Rashi Garg
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 15
Year of Publication: 2015
Authors: Shaifali Gupta, Rashi Garg
10.5120/20630-3228

Shaifali Gupta, Rashi Garg . Scam-Alert: Characterizing Work from Home Scams on Social Networks. International Journal of Computer Applications. 117, 15 ( May 2015), 19-22. DOI=10.5120/20630-3228

@article{ 10.5120/20630-3228,
author = { Shaifali Gupta, Rashi Garg },
title = { Scam-Alert: Characterizing Work from Home Scams on Social Networks },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 15 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 19-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number15/20630-3228/ },
doi = { 10.5120/20630-3228 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:59:29.353297+05:30
%A Shaifali Gupta
%A Rashi Garg
%T Scam-Alert: Characterizing Work from Home Scams on Social Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 15
%P 19-22
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Online social networks have become a favorite platform for marketers and advertisers. Due to the wide reach of these networks and low cost of advertisement, there has been an upsurge of marketing and advertising campaigns on social media. Social networks like facebook, twitter and google+ possess the capability to quickly turn any piece of information viral, thus increasing its impact. However, there do not exist many tools which can tell whether an information circulating on social media is genuine or fraudulent. We confine ourselves to a specific section of marketing campaigns in this work, which is – "Work from home" campaigns. "Work from home" schemes are run with the intention of providing users an attractive option of working from home in return of some remuneration. Unfortunately, many of such "work-from-home" ads floating on social network are actually scams which mislead and cheat on the end user in more than one way. In this work, we present a study of online money making campaigns run on a popular social network – Google+, and propose an approach to distinguish genuine campaigns from scams.

References
  1. ScamWatch Australia, http://www. scamwatch. gov. au/
  2. US government webpage, http://www. consumer. ftc. gov/articles/0175-work-home-usinesses/
  3. ScamVoid, http://www. scamvoid. com/
  4. Naïve Bayes Classifier, http://en. wikipedia. org/wiki/Naive_Bayes_classifier
  5. Cumulative distribution function, http://en. wikipedia. org/wiki/Cumulative_distribution_function
  6. Who Is Lookup,s http://www. whois. com/whois/
Index Terms

Computer Science
Information Sciences

Keywords

Work from home online social networks online security scam hashtags