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  • Detecting Cyber Bullies on Twitter using Machine Learning Techniques


    Author(s): MURALI, Sashaank Pejathaya

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    Abstract:

    The rising use of social networks leads to huge amount of user-generated data. Due to the popularity of social media cyber bullying has become a major problem. Cyber bullying may cause many serious impacts on a person’s life. In the existing system the set of unique features are derived from Twitter such as activity, user and tweet contents. By using these features the cyber bullying words which are presented in the tweets’ content are detected using machine learning algorithms such as Naïve Bayes and Random Forest classifiers. In the proposed work the detection of cyber bully words are integrated into a single unit. The name, gender and age of the cyber bullies will also be detected using feature extraction techniques. In this paper, the Naïve Bayes and Random Forest classifiers are used to detect cyber bullying content that is present in the tweets.



    References:

    [1]. Rui Zhao, Anna Zhou, Kezhi Mao, Automatic Detection of Cyberbullying on Social Networks based on Bullying Features, ICDCN ’16 Article No. 43, January 2016, ACM.

    [2]. Mohammed Ali Al-garadi, Kasturi DewiVarathan, Sri Devi Ravana. Cybercrime detection in online communications: The experimental case of cyberbullying detection in the Twitter network, Computers in Human Behavior 63 (2016) 433-443, Elsevier.

    [3]. Nalini, K., & Sheela, L. J. (2015). Classification of Tweets using text classifier to detect cyber bullying. In Emerging ICT for bridging the future-Proceedings of the 49th Annual convention of the Computer Society of India CSI (Vol. 2, pp. 637-645). Springer.

    [4]. Chavan, V. S., & Shylaja, S. (2015). Machine learning approach for detection of cyber aggressive comments by peers on social media network. In Advances in computing, communications and informatics (ICACCI), 2015 International Conference on (pp. 2354-2358). IEEE.

    [5]. Sanchez, Huascar, and Shreyas Kumar. "Twitter bullying detection." ser. NSDI 12 (2011): 15-15.



    Additional Information

    Article Title: Detecting Cyber Bullies on Twitter using Machine Learning Techniques
    Author(s): MURALI, Sashaank Pejathaya
    Date of Publication: 2017-06-29
    Publication: International Journal of Information Security and Cybercrime
    ISSN: 2285-9225 e-ISSN: 2286-0096
    Digital Object Identifier: 10.19107/IJISC.2017.01.07
    Issue: Volume 6, Issue 1, Year 2017
    Section: Cyber-Attacks Evolution and Cybercrime Trends
    Page Range: 63-66 (4 pages)



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