Bibliometric networks and analytics on gerontology research

Abstract

Purpose

The purpose of this paper is to bibliometrically analyze the gerontology-related research articles for a comprehensive understanding of the gerontology literature.

Design/methodology/approach

This study employed the approach of visual analytics on 32 journals with a total of 99,204 articles published after 2000 to identify the main subfields, keywords, and growth trend. The investigated journals are either open access online or listed in the Social Sciences Citation Index. In addition, the 200 most frequently cited papers were analyzed through bibliographic coupling, co-word, and co-citation analysis.

Findings

The selected most cited papers were mostly published before 2007, and psychiatry and psychology were the top research subfields. Dementia, older adult, and Alzheimer’s disease were the three most frequently occurring keywords, both in Author Keywords and KeyWords Plus. While coupling analysis yielded 12 research groups, co-word analysis classified the most frequently used 20 Author Keywords into two categories. Four research clusters were identified by the co-citation analysis.

Originality/value

This research provides a comprehensive view of the gerontology research as well as an understanding of the subfields and their interrelations. It also provides government departments with directions for formulating and executing policies affecting older people not only in setting academic and professional priorities but also in understanding the key topics related to older people.

Citation

Shen, C.-w., Nguyen, D.T. and Hsu, P.-Y. (2019), "Bibliometric networks and analytics on gerontology research", Library Hi Tech, Vol. 37 No. 1, pp. 88-100. https://doi.org/10.1108/LHT-11-2017-0247