Abstract
Infometrics plays a crucial role in library collection development. It uses quantitative methods to
measure and assess scientific publication outputs. It applies mathematical and statistical
techniques to books and other media, recognising significant works in various disciplines and
identifying future research directions. This study analysed citations from 20 selected master's
theses in Computer Science that were submitted to the Federal University of Technology, Minna,
between 2008 and 2014. Using a bibliometric research design and total enumeration sampling,
data was collected through three document extraction templates covering key study objectives.
The study examined collaboration patterns, document types, and chronological distributions of
cited references. Findings revealed that 53.9% of cited references were multidisciplinary.
Journals (52%) and books (18%) were the most cited document types. Additionally, the cited
references were current and relevant to the research topics at the time of citation. The study
recommends that university library management address budgetary constraints by investing in
multidisciplinary pertinent publications to Computer Science. Furthermore, library acquisition
and collection development committees should prioritise purchasing more scientific journals,
ensuring an optimal balance between journals and other document types in their collections.
Keywords: Collection Development, Infometrics, Citation analysis, University Libraries, Computer Science, Masters' Theses
Publication Date: 2025-02-13