Spammer detection in social networks using deep learning
K. Sivanagi Reddy, V. Harshini, K Maneesha, T. Gyaneshwari · IET conference proceedings. · 2023
In contrast to other social media platforms, Twitter is one of the most notorious and substantial social networking services, as we all know. In the course of the discussion, a user might engage in unauthorized behaviour and send unsolicited communications to disturb the dialogue process. As a result of the intricacy of spammers' communications, spam categorization has gotten increasingly difficult. These types of spam communications are tough to detect. In the previous According to published research, over the last 20 years, many efforts have been made to discover and eliminate spammers and fake accounts. SVR, Some of the deep learning algorithms used in this study are Random Forest and Decision tree. In the proposed technique, we use these algorithms on actual Twitter datasets to detect spam tweets. In this instance, spam is broken down into distinct types of spammers: positive, negative, and moderate.