Algorithmic labeling in hierarchical classifications of publications: Evaluation of bibliographic fields and term weighting approaches

Journal of the Association for Information Science and Technology, vol. 72, pp. 853–869

Abstract

Abstract Algorithmic classifications of research publications can be used to study many different aspects of the science system, such as the organization of science into fields, the growth of fields, interdisciplinarity, and emerging topics. How to label the classes in these classifications is a problem that has not been thoroughly addressed in the literature. In this study, we evaluate different approaches to label the classes in algorithmically constructed classifications of research publications. We focus on two important choices: the choice of (a) different bibliographic fields and (b) different approaches to weight the relevance of terms. To evaluate the different choices, we created two baselines: one based on the Medical Subject Headings in MEDLINE and another based on the Science‐Metrix journal classification. We tested to what extent different approaches yield the desired labels for the classes in the two baselines. Based on our results, we recommend extracting terms from titles and keywords to label classes at high levels of granularity (e.g., topics). At low levels of granularity (e.g., disciplines) we recommend extracting terms from journal names and author addresses. We recommend the use of a new approach, term frequency to specificity ratio, to calculate the relevance of terms.

Authors 3

1. Peter Sjögårde corresponding

   Karolinska Institutet

   Affiliation as printed

   Health Informatics Centre, Department of Learning, Informatics, Management and Ethics Karolinska Institutet Stockholm Sweden

   University Library, Karolinska Institutet Stockholm Sweden

   Health Informatics Centre, Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Sweden

   University Library, Karolinska Institutet, Stockholm, Sweden

2. Per Ahlgren

   Uppsala University

   Affiliation as printed

   Department of Statistics Uppsala University Uppsala Sweden

   Department of Statistics, Uppsala University, Uppsala, Sweden

3. Ludo Waltman Aachen Centre for Science and Technology Studies (CWTS) Leiden University Leiden The Netherlands Centre for Science and Technology Studies

   Leiden University

   Affiliation as printed

   Centre for Science and Technology Studies Leiden University Leiden The Netherlands

   Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands