Spectral influence in networks: An application to Input-Output analysis
Fuente:
arXiv
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866916496866803712 |
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| author | Riane, Nizar |
| author_facet | Riane, Nizar |
| contents | This paper introduces the concepts of spectral influence and spectral cyclicality, both derived from the largest eigenvalue of a graph's adjacency matrix. These two novel centrality measures capture both diffusion and interdependence from a local and global perspective respectively. We propose a new clustering algorithm that identifies communities with high cyclicality and interdependence, allowing for overlaps. To illustrate our method, we apply it to input-output analysis within the context of the Moroccan economy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_02371 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Spectral influence in networks: An application to Input-Output analysis Riane, Nizar Social and Information Networks Combinatorics 05C20, 05C38, 05C85, 05C90 This paper introduces the concepts of spectral influence and spectral cyclicality, both derived from the largest eigenvalue of a graph's adjacency matrix. These two novel centrality measures capture both diffusion and interdependence from a local and global perspective respectively. We propose a new clustering algorithm that identifies communities with high cyclicality and interdependence, allowing for overlaps. To illustrate our method, we apply it to input-output analysis within the context of the Moroccan economy. |
| title | Spectral influence in networks: An application to Input-Output analysis |
| topic | Social and Information Networks Combinatorics 05C20, 05C38, 05C85, 05C90 |
| url | https://arxiv.org/abs/2305.02371 |