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What is Enhanced Algorithm for Fake User Detection about?

This document discusses an enhanced graph-based semi-supervised learning algorithm (EGSLA) to detect fake users on Twitter. The proposed method has four modules: data collection, feature extraction, classification, and decision making. Twitter data collected using Scrapy is used to evaluate the algorithm. The performance of EGSLA is tested against existing techniques like game theory, k-nearest neighbor, support vector machine, and decision tree. Results show EGSLA achieves 90.3% accuracy in identifying fak

Author

karan kalla

Language

EN