{"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/reconocimiento-automatico-del-sarcasmo-esto","title":"Reconocimiento automático del sarcasmo: ¡Esto va a funcionar bien!","arxiv_id":null,"date":"2016-06-01","proceeding":null,"authors":["Mika Hämäläinen"],"abstract":"El objetivo de este trabajo es, en primer lugar, analizar el sarcasmo en el corpus elegido, y en segundo lugar, basándose en este análisis, elaborar un algoritmo de aprendizaje automático supervisado capaz de distinguir entre un input sarcástico y uno no sarcástico. Para ello, se utilizará NLTK, una librería de Python, que permite la construcción de este tipo de algoritmos con facilidad.","url_abs":"https://helda.helsinki.fi/handle/10138/163231","url_pdf":"https://helda.helsinki.fi/bitstream/handle/10138/163231/Mika_Hamalainen_Progradu_2016.pdf?sequence=2&isAllowed=y","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":[],"tasks":[{"task_slug":"es-en","task_name":"es-en"}],"methods":[],"datasets_introduced":[{"slug":"the-best-sarcasm-annotated-dataset-in-spanish","name":"The Best Sarcasm Annotated Dataset in Spanish","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}