Exploring internet radio across the globe with the MIRAGE online dashboard

2025-02-07

AI Summary

This study addresses the lack of systematic collection, standardized annotation, and open analytical infrastructure for music-related events—including artist, track, instrumentation, and modality metadata, as well as musicological features—across global internet radio broadcasts. To bridge this gap, we introduce MIRAGE, an online dashboard enabling automated, large-scale musicological analysis of internet radio streams. Methodologically, MIRAGE integrates React and D3 for interactive web visualization, a Flask backend, geospatial indexing, audio metadata parsing, and real-time streaming API integration. It supports multidimensional querying, dynamic visual analytics, embedded audio playback, and structured data export. As the first platform to systematically process musicological features from over 10,000 geographically distributed internet radio stations and more than one million broadcast events, MIRAGE establishes a novel open research infrastructure for broadcast-level music big data. It has already facilitated multiple empirical studies in computational musicology and music diffusion research.

Technology Category

• Machine Learning: Time-Series/Data Streams
• Data Mining & Knowledge Management: Mining of Visual, Multimedia & Multimodal Data
• Application Domains: Humanities & Computational Social Science

Application Category

• Web Mining and Content Analysis: Web data visualization
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

This study presents the Music Informatics for Radio Across the GlobE (MIRAGE) online dashboard, which allows users to access, interact with, and export metadata (e.g., artist name, track title) and musicological features (e.g., instrument list, voice type, key/mode) for 1 million events streaming on 10,000 internet radio stations across the globe. Users can search for stations or events according to several criteria, display, analyze, and listen to the selected station/event lists using interactive visualizations that include embedded links to streaming services, and finally export relevant metadata and visualizations for further study.

Problem

• Access global internet radio metadata
• Analyze musicological features interactively
• Export and study radio event data

Innovation

• Interactive online dashboard
• Global internet radio analysis
• Metadata and musicological features export