Fake Profile Detection on Twitter using SVM Classifier
V. Aravindh Pashwan1, D. S. Ravi2
1V. Aravindh Pashwan, M. Phil. Scholar, Dept. of Computer Science St. Joseph’s College, Tiruchirappalli, Tamil Nadu, India.
2D. S. Ravi, Associate Professor Dept. of Computer Science St. Joseph’s College, Tiruchirappalli, Tamil Nadu, India.
Manuscript received on 13 January 2021 | Revised Manuscript received on 07 February 2021 | Manuscript Accepted on 15 February 2021 | Manuscript published on 28 February 2021 | PP: 16-20 | Volume-1 Issue-1, February 2021 | A1007021121/2021©LSP
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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Artificial intelligence or machine intelligence were process or actions performed by machine on its own by using the technique “problem solving” and “learning”. Cyber threat is very serios problem in this modern and technology era which lead to huge lose and threat to the human asset and their personal information. The most of human information are gathered and misused from online social media networks by using fake profiles. The aim of the study is to detect the fake user on online social media network – TWITTER, utilizing machine learning algorithm (SVM – Support Vector Machine). This proposed work helps to identify the fake user using twitter user profile attributes, with the aim of improve the security related to OSN- Online Social Media Platforms and achieved the accuracy of 97.33%. In the near future a work may extended by considering many other attributes and implemented through various algorithm to improve in finding the fake users with more accuracy.
Keywords: Fake user, Machine Learning, Online Social Network, Artificial Intelligence.