Social media has become a vital component of our existence, facilitating global connections between individuals. While these platforms provide numerous advantages, they have also exposed vulnerable individuals, particularly children, to online risks. Individuals who prey on children and engage in online harassment utilize the anonymity and wide reach of social media platforms to inflict harm upon others. Previously, these dangers were addressed through the use of manual reporting and human moderators. Users reported suspicious behavior, prompting human moderators to review the content for compliance with platform requirements. Nevertheless, this responsive approach frequently resulted in a delay in taking action, so enabling the spread of harmful content. Researchers have employed machine learning, a type of artificial intelligence that enables computers to learn from data and make predictions, to develop more proactive and effective solutions. The objective is to develop an automated system that can rapidly and efficiently detect online child predators and cyber harassers by employing machine learning methodologies. The proposed machine learning-based approach offers numerous benefits compared to current methods. Initially, it significantly decreases the time it takes to respond, enabling platforms to promptly eliminate dangerous information and individuals. Machine learning algorithms have the capability to identify patterns and links in large data sets that human moderators could overlook, hence enhancing the accuracy of detection. By incorporating machine learning into social media moderation, human moderators may allocate their attention to more complex tasks that need discernment and intervention. This enhances the efficiency of content moderation and decreases the workload of moderators. Utilizing machine learning to detect and prevent online child predators and cyber harassers enhances the level of safety on the internet. Machine learning technologies play a crucial role in combating online abuse due to their proactive nature and high level of accuracy in mitigating social media dangers posed by malicious individuals.

Online safety, Cyber harassment, Child predator detection, Social media moderation, Automated content monitoring, Machine learning