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

محفوظ في:

التفاصيل البيبلوغرافية
الحاوية / القاعدة:	Societies vol. 15, no. 9 (2025), p. 241-267
المؤلف الرئيسي:	Caroleo, Laura
منشور في:	MDPI AG
الموضوعات:	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
الوصول للمادة أونلاين:	Citation/Abstract Full Text + Graphics Full Text - PDF
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الوصف
مستخلص:	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.
تدمد:	2075-4698
DOI:	10.3390/soc15090241
المصدر:	Social Science Database