Identification of Fake Identities on Social Media using various Machine Learning Algorithm
Bharat S. Borkar · International Journal of Advanced Trends in Computer Science and Engineering · 2020
In the current scenario, online social media platforms are the technology's most common and fastest tools for information exchange.The majority of people from all backgrounds expand their time on social networking platforms.An enormous amount of information is developed and shared worldwide through social networks.Such motives have contributed to unauthorized participants engaged in malicious acts against members of the social platform.False account formation is seen on social media as doing more damage than in any other form of Cybercrime.This offense must be identified well before the consumer is told about both the development of the fake identity.Numerous algorithms and approaches have been suggested for the identification of false identities, most of which use the vast amounts of raw data produced by social platforms.In this research, we proposed fake identity detection of social accounts on twitter dataset.Various machine learning algorithms have been used to evaluate the proposed results using NLP techniques.SVM, Fuzzy Random Forest, and Naïve Bayes have used for classification.The experimental analysis shows the effectiveness of the system and how it produces better accuracy than other machine learning algorithms as well as existing systems.