Research trends in text mining: Semantic network and main path analysis of selected journals

Hoon Jung, Bong Gyou Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In this study, network and main path analyses were conducted on 1856 studies related to text mining, by extracting keywords and citation information from the text of each paper. Our findings indicate that research papers on text mining have been published in 45 academic disciplines in the 1980s and 1990s, 105 disciplines in the 2000s, and 171 disciplines in the 2010s. The results show that using text mining as a research topic and method has rapidly increased. We also demonstrate that the main theme of text mining research is discourse and content analysis in the 1980s and 1990s, biology and data mining in the 2000s, and medicine and advanced text mining in the 2010s. Moreover, we examined the main citation path for text mining studies and suggest that the main focus of text mining studies has evolved from information science to information systems and technology management. Additionally, influential papers have been recently published in fields such as architecture and social ecology revealing the wide scope of text mining. This article presents an understanding of previously unexplored research trends in text mining and how these trends shed light on the most influential academic papers in the field.

Original languageEnglish
Article number113851
JournalExpert Systems with Applications
Volume162
DOIs
Publication statusPublished - 2020 Dec 30

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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