Advancing information retrieval: a bibliometric and topic modeling perspective

Purpose This study aims to examine the global research on information retrieval (IR) research from 2015 to 2024, focusing on research trends, institute and author collaboration, leading sources, keyword analysis and future research direction. Design/methodology/approach This study uses the combined method of bibliometrics and topic modeling analysis. The bibliographic data were retrieved from the Scopus database. Analysis tools such as Biblioshiny (primary analysis), Word Cloud, VOSviewer (data visualization), LDAShiny and BERTopic (topic modeling) have been used. A structured keyword string used to collect the data from the database limited to selected bibliographic details. A total of 3,457 details are limited to the journals finally selected between 2025 and 2024 for thematic analysis and conceptual structure evaluations. Findings The inconsistent research growth found during the study period in IR is driven by technological advancements and changes in information dynamics. Bradford’s law indicates 22 journals in Zone 1 (core) contributing 33% of publications, and author productivity is found similar to Lotka’s law. The collaboration pattern indicates a limited global institutional collaboration. Keyword co-occurrence analysis indicates a total of four key clusters related to digital IR, teaching methodologies, technical frameworks and IR systems. The analysis of topic modeling using LDAShiny and BERTopic suggests future research must focus on cognitive science, multilingual retrieval, natural language processing, tailored search engines, semantic search, etc. Practical implications This study examines the global research profile of IR using bibliometric and topic modeling analysis. Future implications include user-centered search, user behavior analysis, multimedia retrieval, big data processing, predictive analytics, semantic search, mobile access and context-aware retrieval. Originality/value This study uniquely identified research in IR using advanced analysis tools, offering valuable insights and methodology to conduct studies in different domains.