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Do We Need a Voice Methodology? Proposing a Voice-Centered Methodology: A Conceptual Framework in the Age of Surveillance Capitalism

Furkejuvvon:
Publikašuvnnas:Societies vol. 15, no. 9 (2025), p. 241-267
Váldodahkki: Caroleo, Laura
Almmustuhtton:
MDPI AG
Fáttát:
Ethics
Surveillance
Communication
Conversation
Machine learning
Methodological problems
User generated content
Models
Ethical standards
Capitalism
Neoliberalism
Social sciences
Sociology
Artificial intelligence
Speech recognition
Ingestion
Social media
Mass media effects
Social discrimination learning
Algorithms
Subjectivity
Personal information
User behavior
Social networks
Governance
Learning algorithms
Methodology
Voice recognition
Natural language processing
Computer platforms
Data collection
Automatic speech recognition
Concept learning
Digital technology
Digital media
Ethical dilemmas
Research methodology
Frame analysis
Mass media
Transformation
Voice analysis
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Abstrákta:This paper explores the rise in voice-based social media as a pivotal transformation in digital communication, situated within the broader era of chatbots and voice AI. Platforms such as Clubhouse, X Spaces, Discord and similar ones foreground vocal interaction, reshaping norms of participation, identity construction, and platform governance. This shift from text-centered communication to hybrid digital orality presents new sociological and methodological challenges, calling for the development of voice-centered analytical approaches. In response, the paper introduces a multidimensional methodological framework for analyzing voice-based social media platforms in the context of surveillance capitalism and AI-driven conversational technologies. We propose a high-level reference architecture machine learning for social science pipeline that integrates digital methods techniques, automatic speech recognition (ASR) models, and natural language processing (NLP) models within a reflexive and ethically grounded framework. To illustrate its potential, we outline possible stages of a PoC (proof of concept) audio analysis machine learning pipeline, demonstrated through a conceptual use case involving the collection, ingestion, and analysis of X Spaces. While not a comprehensive empirical study, this pipeline proposal highlights technical and ethical challenges in voice analysis. By situating the voice as a central axis of online sociality and examining it in relation to AI-driven conversational technologies, within an era of post-orality, the study contributes to ongoing debates on surveillance capitalism, platform affordances, and the evolving dynamics of digital interaction. In this rapidly evolving landscape, we urgently need a robust vocal methodology to ensure that voice is not just processed but understood.
ISSN:2075-4698
DOI:10.3390/soc15090241
Gáldu:Social Science Database