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Parameterless Pruning Algorithms for Similarity-Weight Network and Its Application in Extracting the Backbone of Global Value Chain
oleh: Xing Lizhi, Han Yu
| Format: | Article |
|---|---|
| Diterbitkan: | Sciendo 2021-12-01 |
Deskripsi
With the availability and utilization of Inter-Country Input-Output (ICIO) tables, it is possible to construct quantitative indices to assess its impact on the Global Value Chain (GVC). For the sake of visualization, ICIO networks with tremendous low- weight edges are too dense to show the substantial structure. These redundant edges, inevitably make the network data full of noise and eventually exert negative effects on Social Network Analysis (SNA). In this case, we need a method to filter such edges and obtain a sparser network with only the meaningful connections.