Automated Spammer Detection for Limited Length Social Media

Author:

Mehta Shilpa

Publisher

Springer Nature Singapore

Reference12 articles.

1. Fazil M, Abulaish M (2018) A hybrid approach for detecting automated spammers in Twitter. IEEE Trans Inform Forensics Secur 1–1. https://doi.org/10.1109/TIFS.2018.2825958

2. Soundararajan K, Eranna U, Mehta S, A neural technique for classification of intercepted e-mail communications with multilayer perceptron using BPA with LMS learning. Int J Adv Electr Electron Eng. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.639.3947&rep=rep1&type=pdf

3. Mehta S, Eranna U, Soundararajan K, A fuzzy technique for classification of intercepted communication. Int J Commun Eng Appl IJCEA 3(1): 412–416. ISSN: 2230-8520; e-ISSN: 2230-8539, https://www.researchgate.net/profile/Shilpa_Mehta2/publication/267558855_A_Fuzzy_Technique_for_Classification_of_Intercepted_Communication/links/578f372b08ae9754b7ecc2e1.pdf

4. Tsikerdekis M (2017) Identity deception prevention using common contribution network data. IEEE Trans Inf Forensics Secur 12(1):188–199

5. Lee S, Kim J (2013) Warningbird: a near real-time detection system for suspicious urls in twitter stream. IEEE Trans Dependable Sec Comput 10(3):183–195

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