Automated Information Retrieval from the Bibliographic Metadata: A Way to Facilitate the Systematic Literature Review
Marie Vítová Dušková, Martin Víta · 2022
The aim of this paper is to demonstrate the possible enrichment of the traditional procedure of bibliographic literature review using Natural Language Processing (NLP) methods - automated information retrieval. Our task was to conduct a systematic review of academic literature focused on the classical music audience research in the context of arts management and arts marketing. As a core base, we used bibliographic metadata, extracted from the Scopus database. The limits of the most commonly used methods of bibliographic analysis of the literature, which are co-citation analysis and bibliographic coupling, are well known. Therefore, we also used one of the NLP methods for metadata analysis, which allows automated processing of large numbers of texts to overcome these known problems. Thanks to this, we managed to obtain a higher granularity of the researched topics, to reveal emerging topics and to identify gaps in research. To the best of our knowledge, such an approach to the systematic literature review in the field of social sciences has not yet been applied.