Research on Ecological Imbalance and Sustainable Governance of Algorithmic Platforms

The widespread application of artificial intelligence and algorithmic technologies has gradually made algorithmic platforms an important field for information dissemination, social interaction, and value creation. However, while algorithmic recommendation and data-driven resource allocation mechanisms improve operational efficiency, they may also give rise to problems such as capital concentration, the homogenization of actors’ behavior, and a decline in ecological diversity. Drawing on Bourdieu’s field theory, this paper conceptualizes algorithmic platforms as a new type of technological field jointly constituted by multiple actors, capital distribution, and technological rules, and analyzes the internal relationships among algorithmic habitus, capital concentration, and the erosion of diversity. This study argues that algorithmic platforms shape actors’ practices through data feedback and resource allocation mechanisms and may reinforce existing advantages in the ongoing process of structural reproduction, thereby causing structural imbalance in the platform ecosystem. Accordingly, this paper proposes basic pathways for the ecological governance of algorithmic platforms in terms of capital balance, actor empowerment, diversity protection, open governance, and collaborative governance, aiming to provide a theoretical reference for understanding the structural problems of algorithmic platforms and their sustainable development.