Muse-it: A Tool for Analyzing Music Discourse on Reddit

2025-09-24

AI Summary

This study addresses the lack of systematic analytical tools for music-related discourse on social media by introducing the first end-to-end music discourse analysis framework tailored to Reddit. Methodologically, it integrates large-scale anonymous data crawling and cleaning, NLP-driven topic modeling and clustering, temporal trend analysis, and—innovatively—automated resolution of user-shared music hyperlinks via the Spotify API to retrieve track-level metadata (e.g., genre, release year, acoustic features). The key contributions are: (1) the first automated alignment of de-identified music discussions on Reddit with multidimensional, structured music metadata; (2) a flexible, queryable platform featuring dynamic visualizations and a fully reproducible analytical pipeline. Collectively, this framework significantly enhances the scalability, analytical depth, and accessibility of empirical research on music engagement behaviors.

Technology Category

Natural Language Processing: Discourse, Pragmatics & Argument MiningData Mining & Knowledge Management: Graph Mining, Social Network Analysis & CommunityApplication Domains: Humanities & Computational Social Science

Application Category

Web Mining and Content Analysis: Topic discovery and trackingSocial Networks and Social Media: Social media analysis through the lenses of networksSearch and Retrieval-Augmented AI: Web query analysis, representation and understanding

Abstract

Music engagement spans diverse interactions with music, from selection and emotional response to its impact on behavior, identity, and social connections. Social media platforms provide spaces where such engagement can be observed in natural, unprompted conversations. Advances in natural language processing (NLP) and big data analytics make it possible to analyze these discussions at scale, extending music research to broader contexts. Reddit, in particular, offers anonymity that encourages diverse participation and yields rich discourse on music in ecological settings. Yet the scale of this data requires tools to extract, process, and analyze it effectively. We present Muse-it, a platform that retrieves comprehensive Reddit data centered on user-defined queries. It aggregates posts from across subreddits, supports topic modeling, temporal trend analysis, and clustering, and enables efficient study of large-scale discourse. Muse-it also identifies music-related hyperlinks (e.g., Spotify), retrieves track-level metadata such as artist, album, release date, genre, popularity, and lyrics, and links these to the discussions. An interactive interface provides dynamic visualizations of the collected data. Muse-it thus offers an accessible way for music researchers to gather and analyze big data, opening new avenues for understanding music engagement as it naturally unfolds online.

Problem

• Analyzing large-scale music discourse from Reddit conversations effectively
• Extracting and processing music-related data with metadata integration
• Providing accessible tools for music engagement research using big data

Innovation

• Retrieves Reddit data via user-defined queries
• Performs topic modeling and temporal trend analysis
• Links music metadata and lyrics to discussions