Abstract
Online Social Networks (OSN) like Twitter, Facebook, LinkedIn, Myspace, YouTube and Digg are getting very popular nowadays. They have become a part of everybody’s life as people use to share content like their opinions, feelings with other people. OSNs have also created some serious threats as some people steal personal information of OSN users, similarly some terrorists groups use it as a weapon to achieve certain goals like spread terror among innocent people, brainwashing and recruitment. Therefore, it is the need of the hour to counter such groups. Web mining can be employed to detect terrorism related activities on online social networks. In this paper some major web mining techniques have been discussed which can be helpful to identify such people and terrorism may be countered from OSN. Each technique is discussed thoroughly, and effectiveness along with its pros and cons are also presented. Hence, a number of future research directions are presented which can be undertaken to conduct and improve research in this area.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Berzinji, A., Abdullah, F.S., Kakei, A.H.: Analysis of terrorist groups on facebook. In: 2013 European Intelligence and Security Informatics Conference, Uppsala, p. 221 (2013)
Sadat, M.N., Ahmed, S., Mohiuddin, M.T.: Mining the social web to analyze the impact of Online Social Networks (OSN) on socialization. In: 2014 International Conference on Informatics, Electronics & Vision (ICIEV), Dhaka, pp. 1–6 (2014)
Kunwar, R.S., Sharma, P.: Online Social Networks (OSN): a new vector for cyber attack. In: 2016 International Conference on Advances in Computing, Communication, & Automation (ICACCA) (Spring), Dehradun, pp. 1–5 (2016)
Ashcroft, M., Fisher, A., Kaati, L., Omer, E., Prucha, N.: Detecting Jihadist messages on twitter. In: 2015 European Intelligence and Security Informatics Conference, Manchester, pp. 161–164 (2015)
Mahmood, S.: Online social networks: the overt and covert communication channels for terrorists and beyond. In: 2012 IEEE Conference on Technologies for Homeland Security (HST), Waltham, MA, pp. 574–579 (2012)
Irfan, R., et al.: A survey on text mining in social networks. Knowl. Eng. Rev. 30(2), 157–170 (2015)
Patel, M. R., Sharma, M. G.: A survey on text mining techniques. Int. J. Eng. Comput. Sci. 3(5), 5621–5625 (2014)
Khan, F.H., Bashir, S., Qamar, U.: TOM: twitter opinion mining framework using hybrid classification scheme. Decis. Support Syst. 57, 245–257 (2014)
Medhat, W., Hassan, A., Korashy, H.: Sentiment analysis algorithms and applications: a survey. Ain Shams Eng. J. 5(4), 1093–1113 (2014)
Taboada, M., Brooke, J., Tofiloski, M., Voll, K., Stede, M.: Lexicon-based methods for sentiment analysis. Comput. Linguist. 37(2), 267–307 (2011)
Indrawan, P., Budiyatno, S., Ridho, N.M., Sari, R.F.: Face recognition for social media with mobile cloud computing. Int. J. Cloud Comput.: Serv. Arch. 3(1), 23–35 (2013)
Gaharwar, R.D., Shah, D.B., Gaharwar, G.K.S.: Terrorist network mining: issues and challenges. Int. J. Adv. Res. Sci. Eng. 4(1), 33–37 (2015)
Ball, L.: Automating social network analysis: a power tool for counter-terrorism. Secur. J. (2013). https://doi.org/10.1057/sj.2013.3
Barfar, A., Zolfaghar, K., Mohammadi, S.: A framework for cyber war against international terrorism. Int. J. Internet Technol. Secur. Trans. 3(1), 29–39 (2011)
Parmar, D.N., Mehta, B.B.: Face recognition methods & applications. arXiv preprint arXiv:1403.0485 (2014)
Khan, F.H., Qamar, U., Bashir, S.: Enhanced cross-domain sentiment classification utilizing a multi-source transfer learning approach. Soft Comput. 1–12 (2018). https://doi.org/10.1007/s00500-018-3187-9
Hassan, S., Guha, R.: Honeypots and the attackers bias. In: International Conference on Cyber Warfare and Security, pp. 533–XIII. Academic Conferences International Limited (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Ali, F., Khan, F.H., Bashir, S., Ahmad, U. (2019). Counter Terrorism on Online Social Networks Using Web Mining Techniques. In: Bajwa, I., Kamareddine, F., Costa, A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-13-6052-7_21
Download citation
DOI: https://doi.org/10.1007/978-981-13-6052-7_21
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6051-0
Online ISBN: 978-981-13-6052-7
eBook Packages: Computer ScienceComputer Science (R0)