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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2509.10333 |
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| _version_ | 1866912584928591872 |
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| author | Rondeau, Arthur Wernli, Didier Bouffanais, Roland |
| author_facet | Rondeau, Arthur Wernli, Didier Bouffanais, Roland |
| contents | Although diplomatic communication has long been examined in the social sciences, its network structure remains underexplored. Using the U.S. diplomatic cables released by WikiLeaks in 2010 as a case study, we adopt a network-science perspective. We represent diplomatic interactions as a hypergraph and develop a general, random-walk-based pipeline to evaluate this representation against traditional pairwise graphs. We further evaluate the pipeline on legislative co-sponsorship and organizational email data, finding improvements and empirical evidence that clarifies when hypergraph modeling is preferable to pairwise graphs. Overall, hypergraphs paired with appropriately specified random-walk dynamics more faithfully capture higher-order, group-based interactions, yielding a richer structural account of diplomacy and superior performance on interaction-prediction tasks that enables inferring new diplomatic relationships from existing patterns. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_10333 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Revealing Higher-Order Interactions in Complex Networks: A U.S. Diplomacy Case Study Rondeau, Arthur Wernli, Didier Bouffanais, Roland Social and Information Networks Although diplomatic communication has long been examined in the social sciences, its network structure remains underexplored. Using the U.S. diplomatic cables released by WikiLeaks in 2010 as a case study, we adopt a network-science perspective. We represent diplomatic interactions as a hypergraph and develop a general, random-walk-based pipeline to evaluate this representation against traditional pairwise graphs. We further evaluate the pipeline on legislative co-sponsorship and organizational email data, finding improvements and empirical evidence that clarifies when hypergraph modeling is preferable to pairwise graphs. Overall, hypergraphs paired with appropriately specified random-walk dynamics more faithfully capture higher-order, group-based interactions, yielding a richer structural account of diplomacy and superior performance on interaction-prediction tasks that enables inferring new diplomatic relationships from existing patterns. |
| title | Revealing Higher-Order Interactions in Complex Networks: A U.S. Diplomacy Case Study |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2509.10333 |