Information Retrieval (IR) satisfaction plays a crucial role in shaping user experiences in library systems. This study provides a comprehensive bibliometric analysis of research trends and developments in IR satisfaction from 1968 to 2024, highlighting key themes and contributions in the field. Methods: A comprehensive review of 155 publications from the Scopus database was conducted, using bibliometric tools to analyze publication trends, keyword frequency, author contributions, and thematic mapping. Findings: The study reveals a steady increase in publications from 1968 to 1994, followed by a decline after 2008 and a rise in 2019. The USA and China dominate the field, with minimal collaboration beyond these countries. The primary focus of research is on "information retrieval" and "user satisfaction." New topics include "database systems" and "websites." Originality: This research provides valuable insights into the evolving nature of IR satisfaction, highlighting gaps in global collaboration and the need for further exploration. The study's reliance on Scopus and keyword analysis limits its scope, excluding other databases and emerging trends. Future research should include diverse databases, explore emerging technologies, and examine long-term impacts on user satisfaction across different regions. Academic Value: The knowledge of user satisfaction with library information retrieval is improved by this study. In addition to directing future research in bibliometric trends and providing insightful information for library workers to maximize services in the digital era, it promotes evidence-based enhancements in user-centric information systems.

Aim: This study investigates the challenges students in developing countries face in adapting to internet-based education. It aims to identify key trends, influential contributors, and research gaps, with a particular emphasis on the potential of innovative technologies such as artificial intelligence (AI) and blockchain in addressing digital inequality. Methods: A bibliometric analysis was conducted on 352 scholarly documents sourced from the Scopus database. Advanced analytical tools, including Machine Learning techniques, R programming, Bibliometrix, and VOSviewer, were employed to assess performance indicators, visualize topic clusters, and map the research landscape. Findings: The analysis indicates a growing body of research focused on digital adaptation in education, with substantial contributions from Germany, India, and the UK. Although Hong Kong and Singapore contribute fewer publications, their research garners high citation visibility. Prominent authors such as Choo, Fung, and Wootton have significantly influenced the field. The study identified five major thematic clusters: psychosocial barriers (e.g., internet addiction and academic stress), technological innovations (AI, blockchain, and digital platforms), socioeconomic challenges (connectivity costs and gender disparities), research trends and bibliometric mapping, and multi-stakeholder collaboration involving government, academia, and civil society. A notable research gap exists regarding the practical implementation of AI and blockchain to alleviate these challenges. Originality: This study is among the few to systematically map the global academic discourse on internet adaptation in education within developing regions using bibliometric and machine learning approaches. It introduces an interdisciplinary perspective by combining education, technology, and policy analysis. Academic Value: By synthesizing global research trends and highlighting underexplored areas, particularly the role of emerging technologies, gender disparities, and collaborative strategies, this study provides a valuable reference for scholars, policymakers, and educators. Additionally, by identifying key gaps, it supports evidence-based policy formulation and encourages further localized, gender-sensitive research and pilot interventions to enhance educational equity.