Modeling Science and Technology Systems Through Massive Data Collections

Project: Research

Project Details

Description

The increase in research and development costs, the complexity of technology and the globalization of development have challenged both public and private research and development work. The adequacy of funding and the need to combine resources requires us to look at the innovation system more and more through the interactions of actors. Understanding the interactions requires that we be able to model increasingly complex relationships between the actors. As a result of the project, we better how the whole innovation system operates. The project looked at how we can measure technological developments by utilizing large datasets, combining quantitative and qualitative data, and better understanding the evolution of technologies.
AcronymSA_MST
StatusFinished
Effective start/end date1/09/1531/08/18

Research Output

  • 4 Article
  • 2 Conference article in proceedings

Evaluating technological emergence using text analytics: Two case technologies and three approaches

Ranaei, S., Suominen, A., Porter, A. & Carley, S., 1 Jan 2020, In : Scientometrics. 122, 1, p. 215-247 33 p.

Research output: Contribution to journalArticleScientificpeer-review

Open Access
  • Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective

    Li, M., Porter, A. L. & Suominen, A., 2018, In : Technological Forecasting and Social Change. 129, p. 285-296 12 p.

    Research output: Contribution to journalArticleScientificpeer-review

  • 30 Citations (Scopus)

    Firms' knowledge profiles: Mapping patent data with unsupervised learning

    Suominen, A., Toivanen, H. & Seppänen, M., 1 Feb 2017, In : Technological Forecasting and Social Change. 115, p. 131-142 12 p.

    Research output: Contribution to journalArticleScientificpeer-review

    Open Access
  • 24 Citations (Scopus)