{"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/bleaching-text-abstract-features-for-cross","title":"Bleaching Text: Abstract Features for Cross-lingual Gender Prediction","arxiv_id":"1805.03122","date":"2018-05-08","proceeding":"ACL 2018 7","authors":["Rob van der Goot","Nikola Ljubešić","Ian Matroos","Malvina Nissim","Barbara Plank"],"abstract":"Gender prediction has typically focused on lexical and social network\nfeatures, yielding good performance, but making systems highly language-,\ntopic-, and platform-dependent. Cross-lingual embeddings circumvent some of\nthese limitations, but capture gender-specific style less. We propose an\nalternative: bleaching text, i.e., transforming lexical strings into more\nabstract features. This study provides evidence that such features allow for\nbetter transfer across languages. Moreover, we present a first study on the\nability of humans to perform cross-lingual gender prediction. We find that\nhuman predictive power proves similar to that of our bleached models, and both\nperform better than lexical models.","url_abs":"http://arxiv.org/abs/1805.03122v1","url_pdf":"http://arxiv.org/pdf/1805.03122v1.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":"bleaching-text-abstract-features-for-cross","repo_url":"https://github.com/bplank/bleaching-text","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"gender-prediction","task_name":"Gender Prediction"},{"task_slug":"prediction","task_name":"Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}