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Analyzation and Detection of Cyberbullying: A Twitter Based Indian Case Study

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Abstract

Social networking sites like Facebook and Twitter specially involves large population connected worldwide. Though these social networks aim to bring people from around the world together yet it has its own cons associated with it. With the increase in these Social Networks there is an exponential increase in cybercrimes on these sites. Cyberbullying or Trolling is one such crime where victim is bullied with abuses, personal remarks, false claims and sarcasm on social networking sites and sometimes is traumatized to great extent. There have been many cyberbullying detection methods and systems already developed to cater to the problem but major concern lies on the fact that nearly 80%–90% users on such sites are Indians owing to one of most populous countries in the world, they use Hinglish (Hindi written in English) to communicate mostly on social networking sites majorly Facebook and Twitter. Our research aims at analyzing Cyberbullying content based on Hinglish tweets on one such social network that is Twitter. We analyzed tweets based on textual analysis and performed classification also. Through this we concluded our findings and future scope of work for detection of Cyberbullying on more complex data.

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Notes

  1. 1.

    The Top Six Unforgettable Cyberbullying Cases Ever https://nobullying.com/six-unforgettable-cyber-bullyingcases/.

  2. 2.

    http://www.theverge.com/2015/2/4/7982099/twitter-ceo-sent-memo-taking-personal-responsibility-for-the.

  3. 3.

    https://yourstory.com/2016/07/maneka-gandhi-iamtrolledhelp/.

References

  1. Galán-GarcÍa, P., De La Puerta, J.G., Gómez, C.L., Santos, I., Bringas, P.G.: Supervised machine learning for the detection of troll profiles in twitter social network: application to a real case of cyberbullying. Log. J. IGPL. 24(1), 42–53 (2016)

    Google Scholar 

  2. Al-garadi, M.A., Varathan, K.D., Ravana, S.D.: Cyber-crime detection in online communications: the experimental case of cyberbullying detection in the Twitter network. Comput. Hum. Behav. 63, 433–443 (2016)

    Article  Google Scholar 

  3. Dredge, R., Gleeson, J., de la Piedad Garcia, X.: Presentation on Facebook and risk of cyberbullying victimization. Comput. Hum. Behav. 40, 16–22 (2014)

    Article  Google Scholar 

  4. Alim, S.: Analysis of tweets related to cyberbullying: exploring information diffusion and advice available for cyberbullying victims. Int. J. Cyber Behav. Psychol. Learn. (IJCBPL) 5(4), 31–52 (2015)

    Article  Google Scholar 

  5. Van Hee, C., Lefever, E., Verhoeven, B., Mennes, J., Desmet, B., De Pauw, G., Hoste, V.: Automatic detection and prevention of cyberbullying. In: International Conference on Human and Social Analytics (HUSO 2015), pp. 13–18. IARIA (2015)

    Google Scholar 

  6. Mangaonkar, A., Hayrapetian, A., Raje, R.: Collaborative detection of cyberbullying behavior in Twitter data. In: 2015 IEEE International Conference on Electro/Information Technology (EIT), pp. 611–616. IEEE, May 2015

    Google Scholar 

  7. Van Royen, K., Poels, K., Daelemans, W., Vandebosch, H.: Automatic monitoring of cyberbullying on social networking sites: from technological feasibility to desirability. Telemat. Inf. 32(1), 89–97 (2015)

    Article  Google Scholar 

  8. Dinakar, K., Reichart, R., Lieberman, H.: Modeling the detection of textual cyberbullying. Soc. Mob. Web 11, 02 (2011)

    Google Scholar 

  9. Calvin, A.J., Bellmore, A., Xu, J.M., Zhu, X.: # bully: uses of hashtags in posts about bullying on Twitter. J. Sch. Violence 14(1), 133–153 (2015)

    Article  Google Scholar 

  10. Reynolds, K., Kontostathis, A., Edwards, L.: Using machine learning to detect cyberbullying. In: 2011 10th International Conference on Machine Learning and Applications and Workshops (ICMLA), vol. 2, pp. 241–0244. IEEE, December 2011

    Google Scholar 

  11. Silva, Y.N., Rich, C., Hall, D.: BullyBlocker: towards the identification of cyberbullying in social networking sites. In: The 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), San Francisco, CA, USA (2016)

    Google Scholar 

  12. Dalal, C., Tandon, S., Mukerjee, A.: Insult detection in Hindi (2014)

    Google Scholar 

  13. Joshi, A., Sharma, V., Bhattacharyya, P.: Harnessing context incongruity for sarcasm detection. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, vol. 2, pp. 757–762 (2015)

    Google Scholar 

  14. Xiang, G., Fan, B., Wang, L., Hong, J., Rose, C.: Detecting offensive tweets via topical feature discovery over a large scale Twitter corpus. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, pp. 1980–1984. ACM, October 2012

    Google Scholar 

  15. Hosseinmardi, H., Ghasemianlangroodi, A., Han, R., Lv, Q., Mishra, S.: Towards understanding cyberbullying behavior in a semi-anonymous social network. In: 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 244–252. IEEE, August 2014

    Google Scholar 

  16. Kansara, K.B., Shekokar, N.M.: A framework for cyberbullying detection in social network. Int. J. Curr. Eng. Technol. 5, 494–498 (2015)

    Google Scholar 

  17. Hosseinmardi, H., Mattson, S.A., Rafiq, R.I., Han, R., Lv, Q., Mishra, S.: Detection of cyberbullying incidents on the instagram social network. arXiv preprint arXiv:1503.03909 (2015)

  18. Nandhini, B.S., Sheeba, J.I.: Online social network bullying detection using intelligence techniques. Procedia Comput. Sci. 45, 485–492 (2015)

    Article  Google Scholar 

  19. Wang, X., Gerber, M.S., Brown, D.E.: Automatic crime prediction using events extracted from twitter posts. In: Yang, S.J., Greenberg, A.M., Endsley, M. (eds.) Social Computing, Behavioral - Cultural Modeling and Prediction. SBP 2012. LNCS, vol 7227, pp. 231–238. Springer, Heidelberg, April 2012. https://doi.org/10.1007/978-3-642-29047-3_28

  20. Dadvar, M., Trieschnigg, D., de Jong, F.: Experts and machines against bullies: a hybrid approach to detect cyberbullies. In: Sokolova, M., van Beek, P. (eds.) AI 2014. LNCS (LNAI), vol. 8436, pp. 275–281. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-06483-3_25

    Chapter  Google Scholar 

  21. Vanhove, T., Leroux, P., Wauters, T., De Turck, F.: Towards the design of a platform for abuse detection in OSNs using multimedial data analysis. In: 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013), pp. 1195–1198. IEEE, May 2013

    Google Scholar 

  22. Nalini, K., Sheela, L.J.: Classification of tweets using text classifier to detect cyber bullying. In: Satapathy, S., Govardhan, A., Raju, K., Mandal, J. (eds.) Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India CSI Volume 2. AISC, vol 338. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-13731-5_69

  23. Ghasem, Z., Frommholz, I., Maple, C.: A machine learning framework to detect and document text-based cyberstalking. In: LWA, pp. 348–355 (2015)

    Google Scholar 

  24. Kovacevic, A., Nikolic, D.: Automatic detection of cyberbullying to make Internet a safer environment. In: Handbook of Research on Digital Crime, Cyberspace Security, and Information Assurance, p. 277 (2014)

    Google Scholar 

  25. Nahar, V., Unankard, S., Li, X., Pang, C.: Sentiment analysis for effective detection of cyber bullying. In: Sheng, Q.Z., Wang, G., Jensen, C.S., Xu, G. (eds.) APWeb 2012. LNCS, vol. 7235, pp. 767–774. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-29253-8_75

    Chapter  Google Scholar 

  26. Lau, R.Y., Xia, Y., Ye, Y.: A probabilistic generative model for mining cybercriminal networks from online social media. IEEE Comput. Intell. Mag. 9(1), 31–43 (2014)

    Article  Google Scholar 

  27. Simanjuntak, D.A., Ipung, H.P., Nugroho, A.S.: Text classification techniques used to facilitate cyber terrorism investigation. In: 2010 Second International Conference on Advances in Computing, Control and Telecommunication Technologies (ACT), pp. 198–200. IEEE, December 2010

    Google Scholar 

  28. Chandramouli, R.: Emerging social media threats: technology and policy perspectives. In: 2011 Second Worldwide Cybersecurity Summit (WCS), pp. 1–4. IEEE, June 2011

    Google Scholar 

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Correspondence to Aastha Sahni .

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Sahni, A., Raja, N. (2018). Analyzation and Detection of Cyberbullying: A Twitter Based Indian Case Study. In: Panda, B., Sharma, S., Roy, N. (eds) Data Science and Analytics. REDSET 2017. Communications in Computer and Information Science, vol 799. Springer, Singapore. https://doi.org/10.1007/978-981-10-8527-7_41

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  • DOI: https://doi.org/10.1007/978-981-10-8527-7_41

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