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Community evolution in patent networks: technological change and network dynamics

Community evolution in patent networks: technological change and network dynamics

Gao, Yuan, Zhu, Zhen ORCID: 0000-0003-0258-1454, Kali, Raja and Riccaboni, Massimo (2018) Community evolution in patent networks: technological change and network dynamics. Applied Network Science, 3:26. ISSN 2364-8228 (Online) (doi:https://doi.org/10.1007/s41109-018-0090-3)

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Abstract

When studying patent data as a way to understand innovation and technological change, the conventional indicators might fall short, and categorizing technologies based on the existing classification systems used by patent authorities could cause inaccuracy and misclassification, as shown in literature. Gao et al. (International Workshop on Complex Networks and their Applications, 2017) have established a method to analyze patent classes of similar technologies as network communities. In this paper, we adopt the stabilized Louvain method for network community detection to improve consistency and stability. Incorporating the overlapping community mapping algorithm, we also develop a new method to identify the central nodes based on the temporal evolution of the network structure and track the changes of communities over time. A case study of Germany’s patent data is used to demonstrate and verify the application of the method and the results. Compared to the non-network metrics and conventional network measures, we offer a heuristic approach with a dynamic view and more stable results.

Item Type: Article
Additional Information: © The Author(s) 2018. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Uncontrolled Keywords: Technological change; Temporal networks; Patent data; Louvain community detection method; Overlapping community mapping
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA)
Faculty of Business > Department of International Business & Economics
Last Modified: 25 Aug 2018 01:21
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/21303

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