Detection of Fake and Clone Accounts using Classification and Distance Measure Algorithms
DOI:
https://doi.org/10.15662/IJEETR.2026.0802473Keywords:
Fake Account Detection, Social Media Security, Twitter Analysis, Machine Learning, Naïve Bayes Classifier, Entropy Minimization Discretization (EMD), Data Preprocessing, Classification Algorithms, Misinformation DetectionAbstract
This condition could cause a huge injury to society on the planet. In our research, the fake accounts on Twitter are generally classified as a police technique. We have preprocessed our dataset using an Entropy Minimization Discretization (EMD) supervised technique for numerical options and analyzed the results of the naive mathematician algorithm programme. Social networking sites like Twitter and Facebook draw huge people all over the world, as their lives have been resolved. This quality of social networking is based on the possibility of making false profiles, which end up unfolding malicious material, containing entirely different problems, as well as the possibility of revealing misinformation to its consumers. We gift a classification technique for police work the faux accounts on Twitter. The study identifies a reduced group of the most factors influencing the identification of false accounts on Twitter, followed by entirely different classification techniques for the determined factors. The train accuracy of the model is ninety fifth. Experimental results Demonstrate the competitive classification accuracy of our planned technique. The most popular features are keywords, which are fake accounts identification, classification algorithms, Twitter-based account review
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