{"ID":2871842,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.10333","arxiv_id":"2509.10333","title":"Revealing Higher-Order Interactions in Complex Networks: A U.S. Diplomacy Case Study","abstract":"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.","short_abstract":"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...","url_abs":"https://arxiv.org/abs/2509.10333","url_pdf":"https://arxiv.org/pdf/2509.10333v1","authors":"[\"Arthur Rondeau\",\"Didier Wernli\",\"Roland Bouffanais\"]","published":"2025-09-12T15:13:12Z","proceeding":"cs.SI","tasks":"[\"cs.SI\"]","methods":"[\"Generative Adversarial Network\"]","has_code":false}