Analysis of Spammer Reporting Techniques on Online Social Networks

Consumers' real-world experiences affected by interactions on social networks play a dominant role. With the help of popular social networks, useless information was spread by spammers, with this information real users' time and patience are lost. Two of the most important problems are spam detection and the identification of fake accounts. In this proposed work an analysis of current methods for detecting and preventing Twitter spam was carried out. Twitter uses several techniques for detecting spam, such as classifying Technological posts as spam, URLs as spam, Hot subjects as spam, and Duplicate users. Many other criteria, such as those related to end-users, construction, schematics, and even fleeting aspects, are used to evaluate and contrast various technologies. In this work the above-mentioned two important problems were implemented in determining fake content by considering different aspects and also analysis performed to provide a complete overview of Twitter spam detection and analysis.