Search (2 results, page 1 of 1)

  • × author_ss:"Leydesdorff, L."
  • × author_ss:"Rafols, I."
  • × year_i:[2010 TO 2020}
  1. Leydesdorff, L.; Rotolo, D.; Rafols, I.: Bibliometric perspectives on medical innovation using the medical subject headings of PubMed (2012) 0.00
    0.0025719889 = product of:
      0.036007844 = sum of:
        0.036007844 = weight(_text_:subject in 494) [ClassicSimilarity], result of:
          0.036007844 = score(doc=494,freq=4.0), product of:
            0.10738805 = queryWeight, product of:
              3.576596 = idf(docFreq=3361, maxDocs=44218)
              0.03002521 = queryNorm
            0.33530587 = fieldWeight in 494, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.576596 = idf(docFreq=3361, maxDocs=44218)
              0.046875 = fieldNorm(doc=494)
      0.071428575 = coord(1/14)
    
    Abstract
    Multiple perspectives on the nonlinear processes of medical innovations can be distinguished and combined using the Medical Subject Headings (MeSH) of the MEDLINE database. Focusing on three main branches-"diseases," "drugs and chemicals," and "techniques and equipment"-we use base maps and overlay techniques to investigate the translations and interactions and thus to gain a bibliometric perspective on the dynamics of medical innovations. To this end, we first analyze the MEDLINE database, the MeSH index tree, and the various options for a static mapping from different perspectives and at different levels of aggregation. Following a specific innovation (RNA interference) over time, the notion of a trajectory which leaves a signature in the database is elaborated. Can the detailed index terms describing the dynamics of research be used to predict the diffusion dynamics of research results? Possibilities are specified for further integration between the MEDLINE database on one hand, and the Science Citation Index and Scopus (containing citation information) on the other.
  2. Leydesdorff, L.; Rafols, I.: Local emergence and global diffusion of research technologies : an exploration of patterns of network formation (2011) 0.00
    0.0018186709 = product of:
      0.02546139 = sum of:
        0.02546139 = weight(_text_:subject in 4445) [ClassicSimilarity], result of:
          0.02546139 = score(doc=4445,freq=2.0), product of:
            0.10738805 = queryWeight, product of:
              3.576596 = idf(docFreq=3361, maxDocs=44218)
              0.03002521 = queryNorm
            0.23709705 = fieldWeight in 4445, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.576596 = idf(docFreq=3361, maxDocs=44218)
              0.046875 = fieldNorm(doc=4445)
      0.071428575 = coord(1/14)
    
    Abstract
    Grasping the fruits of "emerging technologies" is an objective of many government priority programs in a knowledge-based and globalizing economy. We use the publication records (in the Science Citation Index) of two emerging technologies to study the mechanisms of diffusion in the case of two innovation trajectories: small interference RNA (siRNA) and nanocrystalline solar cells (NCSC). Methods for analyzing and visualizing geographical and cognitive diffusion are specified as indicators of different dynamics. Geographical diffusion is illustrated with overlays to Google Maps; cognitive diffusion is mapped using an overlay to a map based on the ISI subject categories. The evolving geographical networks show both preferential attachment and small-world characteristics. The strength of preferential attachment decreases over time while the network evolves into an oligopolistic control structure with small-world characteristics. The transition from disciplinary-oriented ("Mode 1") to transfer-oriented ("Mode 2") research is suggested as the crucial difference in explaining the different rates of diffusion between siRNA and NCSC.