1. Abokhodair, N., Yoo, D., McDonald, D.W.: Dissecting a social botnet: growth, content and influence in Twitter. In: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2015, Vancouver, British Columbia, Canada, pp. 839–851 (2015)
2. Adewole, K.S., Anuar, N.B., Kamsin, A., Varathan, K.D., Razak, S.A.: Malicious accounts: dark of the social networks. J. Netw. Comput. Appl. 79, 41–67 (2017)
3. Agarwal, S., Sureka, A.: Characterizing linguistic attributes for automatic classification of intent based racist/radicalized posts on Tumblr micro-blogging website. arXiv preprint arXiv:1701.04931 (2017)
4. Almaatouq, A., Shmueli, E., Nouh, M., Alabdulkareem, A., Singh, V.K., Alsaleh, M., Alarifi, A., Alfaris, A., et al.: If it looks like a spammer and behaves like a spammer, it must be a spammer: analysis and detection of microblogging spam accounts. Int. J. Inf. Secur. 15(5), 475–491 (2016)
5. Benevenuto, F., Magno, G., Rodrigues, T., Almeida, V.: Detecting spammers on Twitter. In: Proceedings of the Conference on Collaboration, Electronic Messaging, Anti-abuse and Spam, CEAS 2010, Redmond, Washington, USA, vol. 6, p. 12 (2010)