  The use of patent citation networks as research tools is becoming
increasingly commonplace in the field of innovation studies. However, these
networks rarely consider the contexts in which these citations are generated
and are generally restricted to a single jurisdiction. Here, we propose and
explore the use of a multilayer network framework that can naturally
incorporate citation metadata and stretch across jurisdictions, allowing for a
complete view of the global technological landscape that is accessible through
patent data. Taking a conservative approach that links citation network layers
through triadic patent families, we first observe that these layers contain
complementary, rather than redundant, information about technological
relationships. To probe the nature of this complementarity, we extract network
communities from both the multilayer network and analogous single-layer
networks, then directly compare their technological composition with
established technological similarity networks. We find that while technologies
are more splintered across communities in the multilayer case, the extracted
communities match much more closely the established networks. We conclude that
by capturing citation context, a multilayer representation of patent citation
networks is, conceptually and empirically, better able to capture the
significant nuance that exists in real technological relationships when
compared to traditional, single-layer approaches. We suggest future avenues of
research that take advantage of novel computational tools designed for use with
multilayer networks.

Physics and Society;Social and Information Networks