Machine Learning Algorithms for Spam Detetction in Social Networks

  • Authors

    • Yenuga Padma
    • Dr. Y.K.Sundara Krishna
    https://doi.org/10.14419/ijet.v7i3.24.22809
  • Machine learning, social networks, spam detection, WEKA and Rapid miner.

  • Abstract

    Most of the web based social systems like Face book, twitter, other mailing systems and social networks are developed for users to share their information, to interact and engage with the community. Most of the times these social networks will give some troubles to the users by spam messages, threaten messages, hackers and so on.. Many of the researchers worked on this and gave several approaches to detect the spam, hackers and other trouble shoots. In this paper we are discussing some tools to detect the spam messages in social networks. Here we are using RF, SVM, KNN and MLP machine learning algorithms across rapid miner and WEKA. It gives the better results when compared with other tools.

     

     

  • References

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  • How to Cite

    Padma, Y., & Y.K.Sundara Krishna, D. (2018). Machine Learning Algorithms for Spam Detetction in Social Networks. International Journal of Engineering & Technology, 7(3.24), 536-540. https://doi.org/10.14419/ijet.v7i3.24.22809

    Received date: 2018-12-02

    Accepted date: 2018-12-02