Computing Systems Research Dominates 51.4% of US LIS School Portfolios

Researchers are increasingly investigating how the structure of academic institutions influences research direction, and a new study sheds light on this dynamic within Library and Information Science (LIS) schools in the United States. Jiangen He and Wen Lou, from the Department of Information Management at East China Normal University, alongside et al., have undertaken the first comprehensive empirical mapping of research portfolios across 44 LIS institutions between 2013 and 2024. Analysing nearly 15,000 publications, their work identifies 16 distinct research themes clustered into three key dimensions , Library and Knowledge Organisation, Human-Centred Technology, and Computing Systems , and reveals significant variations linked to institutional organisation. Importantly, this research demonstrates that while computational approaches are prominent, Human-Centred Technology is actually driving the most significant growth within the field, challenging assumptions of complete computational dominance and offering valuable empirical evidence for strategic planning and accreditation policies.

S. Library and Information Science (LIS) schools. Analysing 14,705 publications authored by 1,264 faculty members from 44 institutions between 2013 and 2024, the research team employed computational methods, including word embeddings and topic modelling, to identify 16 distinct research themes. The study reveals significant differences in research composition across various organizational types, challenging assumptions about field fragmentation. Computer-affiliated schools, for example, cluster tightly around computationally-intensive research and exhibit significant divergence from all other school types, indicating a strong focus on technical aspects of information science. Conversely, independent Information schools demonstrate the greatest research diversity, suggesting a broader intellectual scope and a willingness to explore interdisciplinary connections.

This mixed-method analysis establishes a clear link between institutional positioning and research specialisation, providing valuable insights into the dynamics of academic disciplines. Temporal analysis of LIS schools unveils complex evolutionary dynamics, demonstrating how research priorities are shifting over time. Remarkably, 51.8% are evolving towards both Computing Systems and Library and Knowledge Organization, with many institutions simultaneously shifting along multiple dimensions. Contrary to prevailing narratives of computational dominance, the research establishes that HCT emerged as LIS’s primary growth vector, highlighting the increasing importance of user-centered design and human factors in information science.
These patterns reveal a structured diversification, shaped by but not solely determined by organizational positioning. This work opens new avenues for institutional strategic planning, accreditation policy, and a deeper understanding of LIS’s evolving disciplinary identity amid rapid computational transformation. The findings provide empirical foundations for informed decision-making, enabling academic leaders to optimise resource allocation and curriculum development. Furthermore, the study’s comprehensive documentation of research portfolios and organizational structures offers a valuable resource for accreditation bodies and professional organisations seeking to assess the health and vitality of LIS programs. Ultimately, this research contributes to a more nuanced and evidence-based understanding of the LIS field and its future trajectory.

LIS Research Themes via Topic Modelling reveal key

Scientists undertook a comprehensive computational analysis of 14,705 publications authored by 1,264 faculty members across 44 U. S. Library and Information Science (LIS) schools between 2013 and 2024. This innovative approach enabled the identification of nuanced research specializations within the LIS landscape, moving beyond broad categorisations.

Researchers harnessed the BERTopic algorithm for topic modeling, facilitating the automated discovery of thematic clusters within the publication corpus. The study pioneered a mixed-method analysis, combining quantitative computational results with qualitative interpretation to reveal significant differences in research composition across various organizational types. Specifically, computer-affiliated schools exhibited a strong concentration in computationally-intensive research, demonstrating a statistically significant divergence from other school types. Conversely, independent Information schools showcased the greatest diversity in research portfolios, indicating a broader range of scholarly interests.

To assess temporal trends, the team analysed shifts in research focus within LIS schools over the 2013, 2024 period. Their analysis revealed that 51.4% of schools are evolving towards HCT, while 37.8% are progressing towards CS and another 37.8% towards LKO, many institutions are simultaneously shifting along multiple dimensions. This detailed temporal mapping demonstrates the dynamic nature of LIS research and the complex interplay between different thematic areas. The work challenges prevailing narratives of computational dominance, establishing HCT as the primary growth vector within the field, a finding supported by the quantitative data.

Furthermore, the study’s methodology provides empirical foundations for informed institutional strategic planning and accreditation policy, offering insights into LIS’s evolving disciplinary identity amidst ongoing computational transformation. By systematically mapping the co-occurrence of organizational structures and research portfolios, the research delivers a nuanced understanding of how institutional positioning shapes, and is shaped by, research agendas within the LIS field. This detailed analysis allows for a more informed discussion of field fragmentation and structured diversification, moving beyond anecdotal evidence to provide a data-driven assessment of LIS’s research landscape.

Scientists Results

Scientists meticulously mapped the organizational structures and research portfolios of U. S. Library and Information Science (LIS) schools, analysing 14,705 publications from 1,264 faculty members across 44 institutions between 2013 and 2024. The work reveals substantial variations in research composition based on organizational type, providing a detailed empirical overview of the field’s intellectual landscape.

Experiments demonstrated that COMPUTER-affiliated schools exhibit a strong concentration in computationally-intensive research, differing significantly from all other school types. Independent INFORMATION schools, conversely, displayed the greatest research diversity, indicating a broader range of scholarly pursuits. Temporal analysis revealed dynamic shifts within LIS schools; 51.4% are evolving towards HCT, 37.8% towards CS, and 37.8% towards LKO, with many institutions simultaneously pursuing multiple dimensional shifts. These measurements confirm a complex evolutionary pattern, challenging previous assumptions about field fragmentation and highlighting structured diversification.

Data shows faculty size varies considerably by organizational type, with COMPUTER units averaging 39.2 faculty members (median 36.0), the largest of all groups. INFORMATION units follow with a mean of 28.2 (median 22.0), while COMMUNICATION and EDUCATION units average 18.3 and 12.6 faculty members respectively. ART&SCIENCE units are the smallest, with a mean of 10.6 (median 9.0). Publication output also differs greatly, with COMPUTER units achieving the highest per-faculty productivity at a mean of 25.9 publications (median 16.0, standard deviation 28.3). Results further demonstrate that INFORMATION units have the greatest total publication output, summing 8,837 publications, with a moderate per-faculty rate of 15.7 (median 8.0, standard deviation 18.0). This detailed mapping provides empirical support for institutional strategic planning, accreditation policy, and a deeper understanding of LIS’s evolving disciplinary identity amidst computational transformation.