Applied Research in Quality of Life: A Computational Literature Review

Christian Weismayer ()
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Christian Weismayer: Modul University

Applied Research in Quality of Life, 2022, vol. 17, issue 3, No 12, 1433-1458

Abstract: Abstract As quality of life (QoL) is a highly interdisciplinary topic with a multitude of related research areas, it is beneficial to avail researchers of an overview of the different streams explored in the field. Furthermore, knowledge of prominent sub-domains helps researchers identify links and overlaps between QoL and their fields of interest. To meet these needs, a text-mining-based computational literature review (CLR) of the journal of Applied Research in Quality of Life (ARQOL) was conducted using a machine learning process, latent Dirichlet allocation (LDA), in combination with selection criteria for the decision on the number of topics. The outcome provides the reader with a list of the twelve most heavily discussed topics: 1) consumption & materialism, 2) character strength, 3) spirituality, religiousness & personal beliefs, 4) inequality, 5) leisure & tourism, 6) health related QoL (HRQoL) I, 7) quality of working life (QWL), 8) childhood & adolescence, 9) disparity & development, 10) disorder, 11) community issues, and 12) health related QoL (HRQoL) II. In addition, authors, titles, and publication dates are listed for the top-5-ranked papers that most typify these topics. Subsequent content summaries of these papers reveal more detailed information, such as measurement constructs and theories.

Keywords: Applied Research in Quality of Life (ARQOL); Computational literature review (CLR); Scientometrics; Text mining; Machine learning; Latent Dirichlet allocation (LDA) (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11482-021-09969-9

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