Profiling Online Social Networks for Spam Detection

Authors

  • K. Srinivasan  M.Phil Research Scholar, Department of Computer Science, Sri Jayendra Saraswathy Maha Vidyalaya CAS, Coimbatore, Tamil Nadu, India
  • V. Sureka  Assistant Professor, Department of Computer Science, Sri Jayendra Saraswathy Maha Vidyalaya CAS, Coimbatore, Tamil Nadu, India

Keywords:

OSN, k-NN classifier, Spam detection

Abstract

Social network has become a very general way for internet users to connect and interact online. Users spend sufficiently of time on famous social networks (e.g., Facebook, Twitter, Sina Weibo, etc.), reading news, discussing events and posting messages. Unfortunately, this popularity also attracts a significant amount of spammers who continuously expose malicious behaviour (e.g., post messages containing commercial URLs, following a larger amount of users, etc.), foremost to great misinterpretation and inconvenience on users' social activities. In this paper, a supervised machine learning based solution is proposed for an effective spam detection.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-09-30

Issue

Volume 2, Issue 5, September-October-2017

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
K. Srinivasan, V. Sureka, " Profiling Online Social Networks for Spam Detection, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.488-491, September-October-2017.