Ai-enhanced Digital Belonging: An Exploration of Identity, Trust, And Algorithmic Affectivity

Abstract

This paper explores the transformation of belonging, identity, and trust within AI-driven digital communication environments. In the digital age, identities constructed in social media and online networks have evolved beyond representational forms into algorithmic emotional outputs. Within the framework of “algorithmic affectivity,” this study examines how artificial intelligence influences and redefines individuals’ sense of digital belonging.

Drawing upon Shoshana Zuboff’s theory of surveillance capitalism, Vamık Volkan’s identity formations, and Sherry Turkle’s concept of the digital self, the study employs qualitative analysis to investigate how language, interaction patterns, and algorithmic systems generate emotional dependencies in digital communities. Findings indicate that the feeling of belonging is increasingly mediated by AI-driven interactions rather than human-to-human communication.

The paper argues that belonging has become a technologically mediated emotion, trust is now grounded in algorithmic prediction, and identity is continuously reshaped through data flows. This reconfiguration signals the emergence of an “era of ethical affectivity” within the field of communication studies, urging scholars to reconsider the emotional and moral dimensions of AI-mediated social life.