Discovering Platform Government Research Trends Using Topic Modeling

Sun Young Shin, Chang Kyo Suh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Platform government is a key trend in the 4th industrial revolution. This paper presents an empirical analysis of 5810 articles in the Science Direct Database yielded by a search for the keyword ‘platform government’ from 1998 to 2017. Applying topic modeling to the article abstracts identified 9 key topics that were both representative and meaningful, and essentially corresponded to established sub-fields in platform government research. Measuring the variation of topic distributions over time revealed various rising research trends, such as data analytics and IoT, and a recent increasing popularity of business and governance. The identified key topics and Korean platform government projects were also compared. In conclusion, this study attempted to improve the identification, quantification, and understanding of the themes and trends in platform government over the last 20 years in order to provide a valuable tool for researchers and government agencies to make more informed decisions.

Original languageEnglish
Title of host publicationModel and Data Engineering- 9th International Conference, MEDI 2019, Proceedings
EditorsKlaus-Dieter Schewe, Neeraj Kumar Singh
PublisherSpringer Science and Business Media Deutschland GmbH
Pages67-82
Number of pages16
ISBN (Print)9783030320645
DOIs
StatePublished - 2019
Event9th International Conference on Model and Data Engineering, MEDI 2019 - Toulouse, France
Duration: 28 Oct 201931 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11815 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Model and Data Engineering, MEDI 2019
Country/TerritoryFrance
CityToulouse
Period28/10/1931/10/19

Keywords

  • Government
  • Platform
  • Research trends
  • Text mining
  • Topic modeling

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