zScore | R Documentation |
This function computes the z-score between pairs of technologies from a patent-technology incidence matrix. The z-score is a measure to analyze the co-occurrence of technologies in patent documents (i.e. knowledge combination). It compares the observed number of co-occurrences to what would be expected under the hypothesis that combination is random. A positive z-score indicates a typical co-occurrence which has occurred multiple times before. In contrast, a negative z-socre indicates an atypical co-occurrence. The z-score has been used to estimate the degree of novelty of patents (Kim 2016), scientific publications (Uzzi et al. 2013) or the relatedness between industries (Teece et al. 1994).
zScore(mat)
mat |
A patent-technology incidence matrix with patents in rows and technologies in columns |
Lars Mewes mewes@wigeo.uni-hannover.de
Kim, D., Cerigo, D. B., Jeong, H., and Youn, H. (2016). Technological novelty proile and invention's future impact. EPJ Data Science, 5 (1):1–15
Teece, D. J., Rumelt, R., Dosi, G., and Winter, S. (1994). Understanding corporate coherence. Theory and evidence. Journal of Economic Behavior and Organization, 23 (1):1–30
Uzzi, B., Mukherjee, S., Stringer, M., and Jones, B. (2013). Atypical Combinations and Scientific Impact. Science, 342 (6157):468–472
relatedness.density
, co.occurence
## Generate a toy incidence matrix set.seed(2210) techs <- paste0("T", seq(1, 5)) techs <- sample(techs, 50, replace = TRUE) patents <- paste0("P", seq(1, 20)) patents <- sort(sample(patents, 50, replace = TRUE)) dat <- data.frame(patents, techs) dat <- unique(dat) mat <- as.matrix(table(dat$patents, dat$techs)) ## run the function zScore(mat)
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