• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Artikel
  4. Uncovering Research Streams in the Data Economy Using Text Mining Algorithms
 
  • Details
  • Full
Options
2019
Journal Article
Title

Uncovering Research Streams in the Data Economy Using Text Mining Algorithms

Abstract
Data-driven business models arise in different social and industrial sectors, while new sensors and devices are breaking down the barriers for disruptive ideas and digitally transforming established solutions. This paper aims at providing insights about emerging topics in the data economy that are related to companies' innovation potential. The paper uses text mining supported by systematic literature review to automatize the extraction and analysis of beneficial insights for both scientists and practitioners that would not be possible by a manual literature review. By doing so, we were able to analyze 860 scientific publications resulting in an overview of the research field of data economy and innovation. Nine clusters and their key topics are identified, analyzed as well as visualized, as we uncover research streams in the paper.
Author(s)
Azkan, Can  
Fraunhofer-Institut für Software- und Systemtechnik ISST  
Spiekermann, Markus  
Fraunhofer-Institut für Software- und Systemtechnik ISST  
Goecke, Henry
Institut der Deutschen Wirtschaft
Journal
Technology Innovation Management Review  
Project(s)
DEMAND
Funder
Bundesministerium für Wirtschaft und Energie BMWi (Deutschland)  
Language
English
Fraunhofer-Institut für Software- und Systemtechnik ISST  
Keyword(s)
  • Data Ecosystem

  • Data Economy

  • Digital Economy

  • digital transformation

  • DataMarket

  • Big Data

  • literature review

  • Network Graph

  • Textmining

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024