{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/bayesian-poisson-tucker-decomposition-for","title":"Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations","arxiv_id":"1606.01855","date":"2016-06-06","proceeding":null,"authors":["Aaron Schein","Mingyuan Zhou","David M. Blei","Hanna Wallach"],"abstract":"We introduce Bayesian Poisson Tucker decomposition (BPTD) for modeling\ncountry--country interaction event data. These data consist of interaction\nevents of the form \"country $i$ took action $a$ toward country $j$ at time\n$t$.\" BPTD discovers overlapping country--community memberships, including the\nnumber of latent communities. In addition, it discovers directed\ncommunity--community interaction networks that are specific to \"topics\" of\naction types and temporal \"regimes.\" We show that BPTD yields an efficient MCMC\ninference algorithm and achieves better predictive performance than related\nmodels. We also demonstrate that it discovers interpretable latent structure\nthat agrees with our knowledge of international relations.","url_abs":"http://arxiv.org/abs/1606.01855v1","url_pdf":"http://arxiv.org/pdf/1606.01855v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"bayesian-poisson-tucker-decomposition-for","repo_url":"https://github.com/aschein/bptd","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1606.01855","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}