{"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/authorship-clustering-using-multi-headed","title":"Authorship clustering using multi-headed recurrent neural networks","arxiv_id":"1608.04485","date":"2016-08-16","proceeding":null,"authors":["Douglas Bagnall"],"abstract":"A recurrent neural network that has been trained to separately model the\nlanguage of several documents by unknown authors is used to measure similarity\nbetween the documents. It is able to find clues of common authorship even when\nthe documents are very short and about disparate topics. While it is easy to\nmake statistically significant predictions regarding authorship, it is\ndifficult to group documents into definite clusters with high accuracy.","url_abs":"http://arxiv.org/abs/1608.04485v1","url_pdf":"http://arxiv.org/pdf/1608.04485v1.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":"authorship-clustering-using-multi-headed","repo_url":"https://github.com/douglasbagnall/bog","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}