User's Identification in Social Networks using Ensemble Classifiers

In the modern era, the social life of everyone has become associated with the online social networks. These sites have made a drastic change in the way people pursue their social life. Making friends and keeping in contact with them and their updates has become easier. But with their rapid growth, many problems like fake identity, fake profiles, and online impersonation have also grown. To overcome this problem, writeprint technique is used. This technique is proposed for the user identification by using the different classifiers. Comparison between various classification techniques will be done to find out which one is best in case of detection of user identification whether it is fake or genuine. The data which has been provided for the entire process to be performed is extracted from the Twitter with the help of R package as it provides interface with the Twitter web API (Application Programmable Interface). Various calculations are performed to calculate the accuracy, precision, recall, fmeasure, gmean.