Examining The Concept of Industry 4.0 Studies Using Text Mining and Scientific Mapping Method

Abstract

This paper aims to examine the progress of Industry 4.0 studies worldwide from 2012 to present. The study investigates how these studies progress using text mining and science mapping analysis method and the results are interpreted. Text mining, also referred to as text data mining, roughly equivalent to text analytics, is the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. Using firstly text mining, after secondly scientific mapping methods and the obtained results are interpreted. Text mining with bibliometric analysis method enables a statistical analysis of various data about scientific publications including their country, author(s), cooperation among authors, citations, references, institutions, publication date, and puts forward the general aspect of a certain discipline in the light of obtained statistical results. In other words, the purpose of scientific mapping is to demonstrate structural and dynamic aspects of a scientific research. This study introduces how many indusrty 4.0 related papers were published between the period 2012-2018 regarding SCOPUS data base and their distributions are established with respect to the scope of journals and keywords using scientific mapping analysis with Science Mapping Analysis Software Tool (SciMAT). This package program provides a comprehensive data sorting and opportunity to succeed single-handed distinctive analyis methods for scientific mapping. Moreover, VOSviewer program is also used to put forward citation patterns among authors. Thus, differences between subjects that may have an impact on the revolution of studies concentrated on the concept of industry 4.0 on SCOPUS data base, can be examined.