Association Analysis of Cyberbullying on Social Media using Apriori Algorithm

  • Authors

    • Zuraini Zainol
    • Sharyar Wani
    • Puteri N.E. Nohuddin
    • Wan M.U. Noormanshah
    • Syahaneim Marzukhi
    2018-11-26
    https://doi.org/10.14419/ijet.v7i4.29.21847
  • cyberbullying detection, association rule mining, association analysis, twitter, malay, cybersafety

  • Abstract

    With the phenomenal increase in use of Social Networking Service (SNS) and mobile technology, the consequences of cyberbullying have become an epidemic. More than 80% youth use cell phones making them extremely vulnerable to the abuse and one in three young people have been found victims of this problem. There are many different methods of detection cyberbullying behaviour patterns however rarely any focuses on analysis based on association especially in Malay language. Learning and detecting using association is a natural communication phenomenon that can help to identify abusive content from the hidden corpora, which often goes unnoticed. Association helps to identify trends, rules and patterns of the bullies and detects abusive content considering whole sets rather than focusing on single instances. The current work focuses on detection of cyberbullying instances by association analysis using the Apriori Algorithm. It mainly focuses on detecting bullying and aggressive behaviour on Twitter. Over 80 different patterns with high confidence levels were detected that can be successfully implemented for the detection process. The high confidence levels are indicative of the efficiency of association analysis for cyberbully detection in SNS.

  • References

    1. [1] D. Chatzakou, N. Kourtellis, J. Blackburn, E. D. Cristofaro, G. Stringhini, & A. Vakali, "Measuring #GamerGate: A Tale of Hate, Sexism, and Bullying," Proceedings of the 26th International Conference on World Wide Web Companion, Perth, Australia, 2017.

      [2] Z. Ashktorab, "A Study of Cyberbullying Detection and Mitigation on Instagram," Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion, San Francisco, California, USA, 2016

      [3] D. Chatzakou, N. Kourtellis, J. Blackburn, E. D. Cristofaro, G. Stringhini, & A. Vakali, "Mean Birds: Detecting Aggression and Bullying on Twitter," Proceedings of the 2017 ACM on Web Science Conference, Troy, New York, USA, 2017

      [4] M. Rybnicek, R. Poisel, & S. Tjoa, "Facebook Watchdog: A Research Agenda for Detecting Online Grooming and Bullying Activities," in 2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013, pp. 2854-2859.

      [5] S. P. Kiriakidis & A. Kavoura, "Cyberbullying: A review of the literature on harassment through the internet and other electronic means," Family & community health, Vol. 33, No. 2, pp. 82-93, 2010.

      [6] P. K. Smith, J. Mahdavi, M. Carvalho, S. Fisher, S. Russell, & N. Tippett, "Cyberbullying: Its nature and impact in secondary school pupils," Journal of child psychology and psychiatry, Vol. 49, No. 4, pp. 376-385, 2008.

      [7] A. Ioannou et al., "From risk factors to detection and intervention: A metareview and practical proposal for research on cyberbullying," in 2017 IST-Africa Week Conference (IST-Africa), 2017, pp. 1-8

      [8] A. Nocentini, J. Calmaestra, A. Schultze-Krumbholz, H. Scheithauer, R. Ortega, & E. Menesini, "Cyberbullying: Labels, behaviours and definition in three European countries," Journal of Psychologists and Counsellors in Schools, Vol. 20, No. 2, pp. 129-142, 2010

      [9] Y. Chen, Y. Zhou, S. Zhu, & H. Xu, "Detecting Offensive Language in Social Media to Protect Adolescent Online Safety," presented at the Proceedings of the 2012 ASE/IEEE International Conference on Social Computing and 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust, 2012.

      [10] N. Djuric, J. Zhou, R. Morris, M. Grbovic, V. Radosavljevic, & N. Bhamidipati, "Hate Speech Detection with Comment Embeddings," Proceedings of the 24th International Conference on World Wide Web, Florence, Italy, 2015.

      [11] H. Hosseinmardi, S. A. Mattson, R. Ibn Rafiq, R. Han, Q. Lv, & S. Mishra, "Analyzing Labeled Cyberbullying Incidents on the Instagram Social Network," in Social Informatics: Proceeding of the 7th International Conference, SocInfo 2015, Beijing, China, December 9-12, 2015, Proceedings, T.-Y. Liu, C. N. Scollon, and W. Zhu, Eds. Cham: Springer International Publishing, 2015, pp. 49-66.

      [12] I. Kayes, N. Kourtellis, D. Quercia, A. Iamnitchi, & F. Bonchi, "The Social World of Content Abusers in Community Question Answering," Proceedings of the 24th International Conference on World Wide Web, Florence, Italy, 2015.

      [13] K. Dinakar, R. Reichart, & H. Lieberman, "Modeling the detection of Textual Cyberbullying," The Social Mobile Web, Vol. 11, No. 02, 2011.

      [14] C. Van Hee et al., "Automatic detection and prevention of cyberbullying," Proceeding of the International Conference on Human and Social Analytics (HUSO 2015), 2015, pp. 13-18: IARIA

      [15] M. Dadvar, D. Trieschnigg, & F. de Jong, "Experts and Machines against Bullies: A Hybrid Approach to Detect Cyberbullies," in Advances in Artificial Intelligence: 27th Canadian Conference on Artificial Intelligence, Canadian AI 2014, Montréal, QC, Canada, 2014. Proceedings, M. Sokolova and P. van Beek, Eds. Cham: Springer International Publishing, 2014, pp. 275-281.

      [16] V. Nahar, S. Unankard, X. Li, & C. Pang, "Sentiment Analysis for Effective Detection of Cyber Bullying," Proceeding of the Web Technologies and Applications: 14th Asia-Pacific Web Conference, APWeb 2012, Kunming, China, 2012, pp. 767-774.

      [17] C. Nobata, J. Tetreault, A. Thomas, Y. Mehdad, & Y. Chang, "Abusive Language Detection in Online User Content," Proceedings of the 25th International Conference on World Wide Web, Montrealal, Qubec, Canada, 2016.

      [18] H. Sanchez & S. Kumar, "Twitter bullying detection," ser. NSDI, Vol. 12, pp. 15-15, 2011.

      [19] D. Yin, Z. Xue, L. Hong, B. D. Davison, A. Kontostathis, & L. Edwards, "Detection of harassment on web 2.0," Proceedings of the Content Analysis in the WEB, vol. 2, pp. 1-7, 2009.

      [20] Q. Huang, V. K. Singh, & P. K. Atrey, "Cyber Bullying Detection Using Social and Textual Analysis," presented at the Proceedings of the 3rd International Workshop on Socially-Aware Multimedia, Orlando, Florida, USA, 2014.

      [21] Z. Li, J. Kawamoto, Y. Feng, & K. Sakurai, "Cyberbullying detection using parent-child relationship between comments," Proceedings of the 18th International Conference on Information Integration and Web-based Applications and Services, Singapore, Singapore, (2016).

      [22] V. K. Singh, Q. Huang, & P. K. Atrey, "Cyberbullying detection using probabilistic socio-textual information fusion," in 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2016, pp. 884-887

      [23] J. L. Bigelow, A. Edwards, & L. Edwards, "Detecting Cyberbullying using Latent Semantic Indexing,", Proceedings of the International Workshop on Computational Methods for CyberSafety, Indianapolis, IN, USA, (2016).

      [24] H. Margono, X. Yi, & G. K. Raikundalia, "Mining Indonesian cyber bullying patterns in social networks," Proceedings of the Thirty-Seventh Australasian Computer Science Conference – Vol. 147, Auckland, New Zealand, 2014.

      [25] Z. Zainol, P. N. E. Nohuddin, M. T. H. Jaymes, & S. Marzukhi, "Discovering “interesting†keyword patterns in Hadith chapter documents," Proceeding of the International Conference on Information and Communication Technology, (2016), pp. 104-108, https://doi.org/10.1109/ICICTM.2016.7890785

      [26] R. A. A. Rashid, P. N. E. Nohuddin, & Z. Zainol, "Association Rule Mining Using Time Series Data for Malaysia Climate Variability Prediction," Proceeding of the 5th International Visual Informatics Conference, (2017), pp. 120-130, https://doi.org/10.1007/978-3-319-70010-6_12

      [27] N. A. Harun, M. Makhtar, A. A. Aziz, Z. A. Zakaria, F. S. Abdullah, & J. A. Jusoh, "The Application of Apriori Algorithm in Predicting Flood Areas," International Journal on Advanced Science, Engineering and Information Technology, Vol. 7, No. 3, 2017.

      [28] RapidMiner. Available online: https://rapidminer.com/products/studio/, last visit:29.05.1017

      [29] Z. Zainol, A. M. Azahari, S. Wani, S. Marzukhi, P. N. E. Nohuddin, & O. Zakaria, "Visualizing Military Explicit Knowledge using Document Clustering Techniques " International Journal of Academic Research in Business and Social Sciences, Vol. 8, No. 6, (2018), pp. 1127-1143, available online: http://hrmars.com/hrmars_papers/Visualizing_Military_Explicit_Knowledge_using_Document_Clustering_Techniques.pdf, last visit:25.07.2018

      [30] Z. Zainol, S. Marzukhi, P. N. E. Nohuddin, W. M. U. Noormaanshah, & O. Zakaria, "Document Clustering in Military Explicit Knowledge: A Study on Peacekeeping Documents," in Proceeding of the 5th International Visual Informatics Conference, (2017), pp. 175-184, https://doi.org/10.1007/978-3-319-70010-6_17

      [31] Z. Zainol, P. N. E. Nohuddin, T. A. T. Mohd, & O. Zakaria, "Text Analytics of Unstructured Textual Data: A Study on Military Peacekeeping Document using R Text Mining Package " in Proceeding of the 6th International Conference on Computing & Informatics, (2017), pp. 1-7.

      [32] Z. Zainol, M. T. H. Jaymes, & P. N. E. Nohuddin, "VisualUrText: A Text Analytics Tool for Unstructured Textual Data," Journal of Physics: Conference Series, Vol. 1018, No. 1, (2018), pp. 012011, available online: http://iopscience.iop.org/article/10.1088/1742-6596/1018/1/012011/meta, last visit: 28.07.2018

  • Downloads

  • How to Cite

    Zainol, Z., Wani, S., Nohuddin, P. N., Noormanshah, W. M., & Marzukhi, S. (2018). Association Analysis of Cyberbullying on Social Media using Apriori Algorithm. International Journal of Engineering & Technology, 7(4.29), 72-75. https://doi.org/10.14419/ijet.v7i4.29.21847

    Received date: 2018-11-27

    Accepted date: 2018-11-27

    Published date: 2018-11-26