No. 2017-12 - Early identification of important patents through network centrality

Date: 03 November 2017

One of the most challenging problems in technological forecasting is to identify as early as possible those technologies that have the potential to lead to radical changes in our society. In this paper, we use the US patent citation network (1926-2010) to test our ability to early identify a list of historically significant patents through citation network analysis. We show that in order to e?ectively uncover these patents shortly after they are issued, we need to go beyond raw citation counts and take into account both the citation network topology and temporal information. In particular, an age-normalized measure of patent centrality, called rescaled PageRank, allows us to identify the significant patents earlier than citation count and PageRank score.

François Lafond Manuel Sebastian Mariani Matúš Medo

Complexity Economics

Early identification of important patents through network centrality


Type: inet-working-paper

Mariani, M. S., Medo, M. & Lafond, F. (2017) 'Early identification of important patents through network centrality'. INET Oxford Working Paper No. 2017-12


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