TY  - JOUR
N2  - We develop a model of scientific creativity and test it in the field of rare diseases. Our model is based on the results of an in-depth case study of the Rett Syndrome. Archival analysis, bibliometric techniques and expert surveys are combined with network analysis to identify the most creative scientists. First, we compare alternative measures of generative and combinatorial creativity. Then, we generalize our results in a stochastic model of socio-semantic network evolution. The model predictions are tested with an extended set of rare diseases. We find that new scientific collaborations among experts in a field enhance combinatorial creativity. Instead, high entry rates of novices are negatively related to generative creativity. By expanding the set of useful concepts, creative scientists gain in centrality. At the same time, by increasing their centrality in the scientific community, scientists can replicate and generalize their results, thus contributing to a scientific paradigm. 
KW  - Creativity;  Co-authorship network; Scientific collaboration; Bibliometric indicators; Biomedical research; Qualitative and quantitative method 
JF  - Scientometrics
IS  - 1
VL  - 89
PB  - Springer
EP  - 420
SN  - 0138-9130
AV  - none
ID  - eprints1040
SP  - 397
Y1  - 2011/07//
A1  - Frigotto, M. Laura
A1  - Riccaboni, Massimo
UR  - http://dx.doi.org/10.1007/s11192-011-0431-9
TI  - A few special cases: scientific creativity and network dynamics in the field of rare diseases
ER  -