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426846

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

Article

Last updated: 11 May 2025

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Subjects

-

Tags

Artificial Intelligence

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.

DOI

10.21608/asc.2025.351475.1033

Keywords

Anonymous Communication, Schema, validation, Auth.js, Zod, Spam & Fraud Detection, Feedback Collection, Content Moderation, Next.js, Foul Language Detection

Authors

First Name

Siddhesh

Last Name

Mengade

MiddleName

-

Affiliation

Computer Engineering, Genba Sopanrao Moze College of Engineering

Email

pentosid@gmail.com

City

-

Orcid

-

First Name

Pranjali

Last Name

Chopade

MiddleName

-

Affiliation

Computer Engineering, Genba Sopanrao Moze College of Engineering

Email

chopadepranjali3@gmail.com

City

Pune

Orcid

-

First Name

Parth

Last Name

Tate

MiddleName

-

Affiliation

Computer Engineering, Genba Sopanrao Moze College of Engineering

Email

parthtate575@gmail.com

City

Pune

Orcid

-

First Name

Shraddha

Last Name

Patil

MiddleName

-

Affiliation

Computer Engineering, Genba Sopanrao Moze College of Engineering

Email

shraddhajpatil93@gmail.com

City

Pune

Orcid

-

Volume

16

Article Issue

1

Related Issue

53415

Issue Date

2025-01-01

Receive Date

2025-01-08

Publish Date

2025-01-01

Page Start

19

Page End

32

Print ISSN

1687-8515

Online ISSN

2682-3578

Article File

ASC_Volume 16_Issue 1_Pages 19-32.pdf

PDF . 368.2kB

Link

https://asc.journals.ekb.eg/article_426846.html

Detail API

http://journals.ekb.eg?_action=service&article_code=426846

Order

426,846

Type

Original Article

Type Code

1,549

Publication Type

Journal

Publication Title

Journal of the ACS Advances in Computer Science

Publication Link

https://asc.journals.ekb.eg/

MainTitle

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

Details

Type

Article

Created At

11 May 2025