Unveiling latent relations in the photonics techno-economic complex system

S Samoili, R Righi, M Lopez-Cobo, M Cardona… - Italian Workshop on …, 2018 - Springer
S Samoili, R Righi, M Lopez-Cobo, M Cardona, G De Prato
Italian Workshop on Artificial Life and Evolutionary Computation, 2018Springer
The aim of this study is to capture a technology's pathway by identifying emerging
subdomains in a complex system of economic processes. The objective is to uncover
indirect latent relations among agents interacting in a specific techno-economic segment
(TES). A methodology, including an “Extract-Transform-Load”(ETL) process preceding the
two steps aimed for analysis, is developed to analyse a TES regarding R&D economic
processes of the photonics technology. In the first step, economic relevant R&D activities …
Abstract
The aim of this study is to capture a technology’s pathway by identifying emerging subdomains in a complex system of economic processes. The objective is to uncover indirect latent relations among agents interacting in a specific techno-economic segment (TES). A methodology, including an “Extract-Transform-Load” (ETL) process preceding the two steps aimed for analysis, is developed to analyse a TES regarding R&D economic processes of the photonics technology. In the first step, economic relevant R&D activities (EU funded projects and patents) are analysed through a multilayer network (MLN) of agents, considering their interactions in three dimensions, which represent occurred and latent relationships: co-participations in economic activities, common geographical location provenance, common use of technological terms. Then communities are detected (Infomap Algorithm for MLN), and their ongoing within and between connections are studied, as potential factors that affect the entire structured technological ecosystem. In the second step, technological subdomains associated with method-oriented and application-oriented activities are identified through topic modelling. Using the MLN structure, the textual information of the corpus of documents describing the aforementioned economic R&D activities is associated to agents, and the topic model (Latent Dirichlet Allocation) uncovers additional potential semantic connections among them. Subsequently, the results of the MLN community detection and of the topic modelling based on the descriptions of economic activities are considered. Hence, the latent relations of agents are mapped.
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