Decoding Algorithms for a Sustainable Future: A Bibliometric Analysis of Social Media Studies

Abstract

This study examines the influence of social media algorithms on through a bibliometric and thematic analysis of recent scholarly literature. The investigation reveals a rapidly growing and highly interdisciplinary research domain that integrates sustainability with advanced digital technologies, particularly artificial intelligence, machine learning and big data analytics. Publication trend shows consistent annual growth, with a sharp rise in output from 2020 onwards and a peak in 2025, indicating that the field has transitioned from a nascent to an expansion phase. Keyword analysis highlights dominant themes such as “sustainability”, and “sustainable development,” “social media,” “algorithms,” and “sentiment analysis,” underscoring a shift towards algorithmically mediated, data driven approaches to understanding sustainable behavior. The study further identifies that research is concentrated in a few key outlets, characterized by moderate international collaboration, and driven by institutions in Asis and the Middle East, with uneven citation impact across regions. Emerging trends point toward applied, problem solving research on climate change, big data, healthcare, supply chains, and urban system. The findings suggest that social media algorithms are increasingly shaping the visibility, framing and reinforcement of sustainable choices, but also raise concerns about greenwashing, echo chambers and the need for more transparent, ethically designed “sustainable algorithms.” The paper concludes by calling for more theory driven, behaviorally grounded research and stronger policy oriented collaboration to harness algorithmic infrastructures for genuine sustainability outcomes rather than merely symbolic or consumerist green behaviors.