Research Areas in Big Data Analytics Studies

Luka Tomat ()
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Luka Tomat: University of Ljubljana

A chapter in Economy, Finance and Business in Southeastern and Central Europe, 2018, pp 785-795 from Springer

Abstract: Abstract Among the areas, which drive the economies of the modern world, big data analytics plays a significant part. Numerous scientific papers have been published in that field in the past 10 years, but only a few have investigated the research areas of big data analytics studies at the global level. To clarify the current state of the research and knowledge structure, this study carries out a co-occurrence analysis aiming to identify the clusters of main terms that co-occur in the examined papers and provide graphical visualization of relationships between those terms. Publications used in this study were determined on the basis of bibliometric analysis of the big data analytics papers published between 2000 and 2015 in all journals indexed by the Web of Science database. Presented study delivers an overview of the recent bibliometric research in the field and explains the used methodology. The implementation of the co-occurrence analysis is described deeply in the presented paper. The terms (sequences of nouns and adjectives ending with a noun) were extracted from the titles and the abstracts of the selected papers, and special software for visualizing bibliometric networks (VOSviewer) was used to create the term map, where the distances between terms signify the amount of their co-occurrences in the analyzed papers. Two clusters of significant size were indicated, each of them representing a major area of the research studies on the big data analytics. At the end the interpretation of the results, the discussion, and the avenues of further research are given. The proposed study supports the researchers in the area with the insights that allow them better understanding of the current state and the trends in the big data analytics research.

Keywords: Big data; Big data analytics; Bibliometrics; Co-occurrence analysis; Text mining; Visualization (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-319-70377-0_54

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DOI: 10.1007/978-3-319-70377-0_54

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