The Analysis of Resilientnet-Realtime Disaster Response System
Year: 2024
Type: article
Abstract: Responding to India's urgent need for effective disaster management, proposed framework ResilientNet, an innovative system leveraging real-time big data processing and advanced AI technologies. ResilientNet gathers diverse multimedia content from a wide range of social media services, including Twitter, Instagram, Facebook, etc., and utilises the GEMINI API, enabling comprehensive analysis and verification. Data is stored in the NEO4J database and visually represented on a user-friendly website dashboard for easy accessibility and insights. This research explores the efficacy of crowdsourced fact- checking, contributing to a novel disaster-focused tweet verification system. ResilientNet's amalgamation of crowdsourcing and AI creates a comprehensive graph of critical metrics and trends, enabling authorities to counter misinformation and direct disaster response efforts efficiently.
Source: INTI JOURNAL.
Institution: University of Mumbai
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4404192576