INTERNATIONAL RESEARCH JOURNAL OF SCIENCE ENGINEERING AND TECHNOLOGY

( Online- ISSN 2454 -3195 ) New DOI : 10.32804/RJSET

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PREDICTION OF CYBERBULLYING USING RANDOM FOREST CLASSIFIER: A REVIEW

    2 Author(s):  LAKHDEEP KAUR,DR. SONIA VATTA

Vol -  9, Issue- 2 ,         Page(s) : 25 - 32  (2019 ) DOI : https://doi.org/10.32804/RJSET

Abstract

With the advancement of technology, social media is a basic need of the modern world. Due to increasing the popularity of social media, cyberbullying is also becoming a big concern. If a person harasses another person using digital appliances like mobile phones, internet or emails is called cyberbullying. The bully person can be very intelligent, he knows all the schemes to create problem to the victim and can easily hide his identity. The cyberbullying is very difficult to identify because the bully messages are very less as compared to the normal messages. The classification and feature extraction of the data set is very difficult. But Data mining is the best and popular technology for classification and regression. It is the process by which useful information and patterns are extracted from a large amount of data stored in the databases. Data Mining is also known as knowledge discovery process as knowledge is being extracted or patterns are analyzed which is very useful to collect data. It is very important to note that the exactness and availability of the results will rely on the standard of information investigation and the nature of the suspicious user. In the existing work, the Naïve Bayes classifier has been used on the cyberbullying. But there is huge no. of limitations for classifying the cyberbullying like accuracy, precision time, recall, execution time. In this review paper, the Random Forest classifier will be described for the cyberbullying. It is expected that Random Forest classifier will high accuracy and high sensitivity as compared to Naïve Bayes.

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