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</script>Please, cite us: Luis Gasco Sánchez, Darryl Estrada Zavala, Eulàlia Farré-Maduell, Salvador Lima-López, Antonio Miranda-Escalada, and Martin Krallinger. 2022. The SocialDisNER shared task on detection of disease mentions in health-relevant content from social media: methods, evaluation, guidelines and corpora. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, pages 182–189, Gyeongju, Republic of Korea. Association for Computational Linguistics. @inproceedings{gasco2022socialdisner, title = "The {S}ocial{D}is{NER} shared task on detection of disease mentions in health-relevant content from social media: methods, evaluation, guidelines and corpora", author = "Gasco S{\'a}nchez, Luis and Estrada Zavala, Darryl and Farr{\'e}-Maduell, Eul{\`a}lia and Lima-L{\'o}pez, Salvador and Miranda-Escalada, Antonio and Krallinger, Martin", booktitle = "Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop {\&} Shared Task", month = oct, year = "2022", address = "Gyeongju, Republic of Korea", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.smm4h-1.48", pages = "182--189" } SocialDisNER Annotation Guidelines: These guidelines describe the annotation and standardization process of the SocialDisNER corpus, a collection of 9,500 tweets written in Spanish by patients and medical professionals annotated with disease mentions. SocialDisNER resources: Web SocialDisNER Corpora For further information, please visit https://temu.bsc.es/socialdisner/ or email us at encargo-pln-life@bsc.es
Funded by the Plan de Impulso de las Tecnologías del Lenguaje (Plan TL).
socialdisner, social media, NER, twitter, text mining, Spanish, NLP, diseases
socialdisner, social media, NER, twitter, text mining, Spanish, NLP, diseases
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