This exercise requires an understanding of both how the context of digitalisation in the public sector has evolved in relation to technological change and the identification of specific ALMPs that are more sensitive to digitalisation.
The purpose of this article is to develop a conceptual framework that sets out the linkages that exist between digitalisation and active labour market policies (ALMPs).īased on a narrative literature review, this article seeks to connect two research streams, namely that relating to ALMPs and that relating to digitalisation in the public sector. The contribution of the article is to demonstrate how the publication network is formed in this particular field of research, and how the content of abstracts can be automatically analyzed to provide a set of research topics for quick understanding and application in future projects. The results presented met three criteria: (1) literature review for a research area, (2) analysis and classification of journals, and (3) analysis and classification of academic and individual research teams. The computational literature review is an integral part of a broader literature review process. All research was conducted according to the standards of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses in a fully computerized way. The Latent Dirichlet Allocation method, chosen for modeling, required the following stages: 1) data cleansing, and 2) data modeling into topics for coherence and perplexity analysis. A total of 9649 studies were identified, which were analyzed using probabilistic topic modeling procedures within a machine learning approach.
Thus, a review was performed on two online databases (Scopus and ISI Web of Science) from 2012 to 2019.
This research aims to illustrate the potential use of concepts, techniques, and mining process tools to improve the systematic review process.
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