Facilitating Anonymous Communication on Social Networks via AI-Driven Content Moderation

Document Type : Original Article

Authors

Computer Engineering, Genba Sopanrao Moze College of Engineering

Abstract

The Anonymous Messaging Application (Anonify) is designed to provide a secure platform for users to send and receive anonymous feedback, messages, or questions, fostering open dialogue in academic, professional, and social settings. The primary objective of this project is to address the need for a safe space where individuals can express their thoughts without fear of judgment or retribution, while ensuring robust content moderation to prevent misuse. To achieve this, Anonify leverages modern technologies such as Next.js for seamless server-side rendering, Natural Language Processing (NLP) for real-time content analysis, Auth.js for secure user authentication, and Tailwind CSS for an intuitive user interface. The methods employed include the integration of an AI-powered moderation engine that uses machine learning algorithms to detect and filter inappropriate content, such as abusive language, spam, or malicious intent. NLP models are utilized to identify patterns associated with bullying or fraudulent behavior, while fraud detection mechanisms monitor for repeated misuse attempts. These measures ensure that the platform maintains a respectful and constructive environment for users.
The results demonstrate Anonify’s ability to effectively moderate content in real-time, filtering out harmful messages while allowing constructive feedback to reach the intended recipients. The application successfully balances anonymity with accountability, providing a secure space for open communication without compromising user safety.
Thus Anonify represents a significant step forward in anonymous communication platforms, addressing the challenges of unregulated online environments. By integrating advanced AI moderation and user-friendly design, the application promotes constructive dialogue, enhances personal and professional relationships, and ensures a safe, anonymous feedback system.

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