1. Mr. Zahir Pathan
2. Mr. Shridhar Deshpande
3. Miss. Sakshi Bhongale
4. Miss. Pranali Dhamale
Abstract
In the present generation online social networks have become increasingly popular, the rapid growth of OSNs and the massive amount of personal data of its subscribers have attracted attackers, and imposters to steal personal data, share false news, and spread malicious activities. SVM-NN, is proposed to provide efficient detection for fake Twitter accounts and bots, feature selection and dimension reduction
techniques were applied.
Machine learning classification algorithms were used to decide the target accounts identity real or fake; those algorithms were support vector machine, neural Network, and our newly developed algorithm, SVM-NN. The proposed algorithm uses less number of features, while still being able to correctly classify about 98% of the accounts of our training dataset.
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