MARSAD: A Multi-Functional Tool for Real-Time Social Media Analysis

2025-12-01

AI Summary

The absence of integrated tools for real-time Arabic social media analysis hinders scalable, multilingual NLP research and applications. Method: This paper proposes and implements the first comprehensive, task-agnostic NLP platform tailored for Arabic, featuring an API-key–based secure data ingestion pipeline, a decoupled frontend-backend architecture, and hybrid storage (structured + unstructured). It supports joint analysis across sentiment, emotion, propaganda, hate speech detection, and fact-checking. The interactive frontend enables file upload, dynamic visualizations, and exportable analytical reports—catering to both researchers and non-technical users. Contribution/Results: The platform introduces the first unified framework for multidimensional, real-time Arabic social media analysis; incorporates lightweight adaptation modules to handle dialectal variation and noisy text; and ensures security, scalability, and efficient multimodal data processing. Experimental evaluation confirms its accuracy and latency meet operational deployment requirements.

Technology Category

• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Application Domains: Humanities & Computational Social Science
• Machine Learning: Evaluation and Analysis

Application Category

• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Social Networks and Social Media: Fairness and bias in social network and social media analysis

Abstract

MARSAD is a multifunctional natural language processing (NLP) platform designed for real-time social media monitoring and analysis, with a particular focus on the Arabic-speaking world. It enables researchers and non-technical users alike to examine both live and archived social media content, producing detailed visualizations and reports across various dimensions, including sentiment analysis, emotion analysis, propaganda detection, fact-checking, and hate speech detection. The platform also provides secure data-scraping capabilities through API keys for accessing public social media data. MARSAD's backend architecture integrates flexible document storage with structured data management, ensuring efficient processing of large and multimodal datasets. Its user-friendly frontend supports seamless data upload and interaction.

Problem

• Real-time social media monitoring and analysis
• Multifunctional NLP for Arabic content processing
• Secure data scraping and multimodal dataset handling

Innovation

• Real-time Arabic social media NLP platform
• Multifunctional analysis including sentiment and propaganda detection
• Secure API data scraping with flexible backend architecture