Open AccessTwitter Bots Detection Using Machine Learning Techniques
Author(s) -
S G Deekshith
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.36637
Subject(s) - computer science , identity theft , support vector machine , identity (music) , intrusion detection system , random forest , intrusion , machine learning , social network (sociolinguistics) , computer security , artificial intelligence , data mining , social media , internet privacy , world wide web , physics , geochemistry , acoustics , geology
The social network, a crucial part of our life is plagued by online impersonation and fake accounts. Fake profiles are mostly used by the intruders to carry out malicious activities such as harming person , identity theft and privacy intrusion in Online Social Network(OSN). Hence identifying an account is genuine or fake is one of the critical problem in OSN .In this paper we proposed many classification algorithm like Support Vector Machine algorithm ,KNN, and Random Forest algorithm. It also studies the comparison of classification methods on Spam User dataset which is used to select the best.