Digital Sustainability Intelligence and Social Media Analytics: A Bibliometric Analysis

The combination of artificial intelligence (AI) and social media analytics provides the means to recognize and predict sustainability-related trends from large volumes of publicly available user data. Its adoption, however, is constrained by concerns about privacy, ethics, and transparency. This bibliometric study analyzed 559 documents from 274 sources, written by 3,414 authors between 2020 and 2025, using RStudio. The annual growth rate was 3.27%, with an average of 71.57 citations per document. Publications in IEEE Access grew significantly, while Scientific Reports and Heliyon grew after 2023. Deep learning, big data, healthcare, privacy, federated learning, and explainable AI were at the center of AI and machine learning research. The findings of this study can help researchers, managers, and policymakers make ethical, data-driven sustainability decisions.