Author: VPInstitute

  • Measuring tech emergence: A contest

    Highlights Thirteen teams strive to distinguish emerging research topics in synthetic biology. Analyses of ten years of article abstracts predict topics in the next two years. Augmenting, consolidating, embedding, and clustering text help detect emergence. Analyses of citation patterns and research networking also help discern emergence. We conducted a contest to predict highly active research…

  • Parallel or Intersecting Lines? Intelligent Bibliometrics for Investigating the Involvement of Data Science in Policy Analysis

    Efforts to involve data science in policy analysis can be traced back decades but transforming analytic findings into decisions is still far from straightforward task. Data-driven decision-making requires understanding approaches, practices, and research results from many disciplines, which makes it interesting to investigate whether data science and policy analysis are moving in parallel or whether…

  • Parameter tuning Naïve Bayes for automatic patent classification

    In an era of exponential technological growth, business intelligence professionals are more in need than ever of an organized patent landscape in which to conduct technology forecasting and industry positioning. However, the construction of such a system requires time and trained experts, both of which are expensive investments for such a small part of any…

  • Do national funding organizations properly address the diseases with the highest burden? – Observations from China and the UK (Full-Text)

    Recent years have witnessed an incipient shift in science policy from a focus mainly on academic excellence to a focus that also takes into account “societal impact”. This shift raises the question as to whether medical research has given proper attention to the diseases imposing the greatest burden on society. Therefore, with the aim of…