Congreso, coloquio o simposioInfoling 2.17 (2021)

Título:CFP ProfNER shared task: Identification of professions & occupations in Spanish Health-related Social Media (SMM4H at NAACL) (ProfNER SMM4H-NAACL)
Entidad organizadora:BSC
Lugar de celebración:Mexico City, México
Fecha de celebración:10 de junio de 2021
Circular Nº:1
Contacto:Martin Krallinger (BSC), krallinger.martin@gmail.com
Descripción

We are organizing the first shared task specifically focusing on named entity recognition of professions & occupations in Social Media in Spanish. Specifically, we focus on Twitter data related to Covid-19 and lock-downs. ProfNER is part of The Social Media Mining for Health Applications (#SMM4H) Shared Task 2021.


 


Task motivation


Some workers are at the forefront of the battle against the COVID-19 pandemic. Detecting vulnerable occupations is critical to prepare preventive measures related to exposure to the virus as well as indirect mental health issues due to fear of infection, confinement, etc.


NLP systems benefit from recent NLP technologies such as transformers, novel language technologies and transfer learning and from the vast production of real-time data in social media.


Following the previous organization of shared task with high impact with a considerable number of participants [Cantemist], [CodiEsp], [Meddocan] we are organizing the ProfNER track. It promotes the development of profession & occupation-related text mining resources in Spanish social media due to the special relevance of professions in the definition of at-risk groups.


Systems capable of automatically processing social media texts are of interest to the medical user community, researchers, the pharmaceutical industry as well as patients. The detection of profession & occupation information is relevant for general NLP, occupational data mining, etc.


Competing systems have the potential to generalize to alike use cases in other content types such as medical reports and in other languages.


 


The ProfNER sub-tracks


Tweet binary classification: Participants must determine whether a tweet contains a mention of occupation, or not.


 


NER offset detection and classification: Participants must find the beginning and end of occupation mentions and classify them in the corresponding category


 


Key information


ProfNER web: https://temu.bsc.es/smm4h-spanish/


Datasets: https://doi.org/10.5281/zenodo.4309356

Registration: https://forms.gle/1qs3rdNLDxAph88n6


 


Important dates


Dec, 15: Training & Development set release


Feb, 15: Validation set submission due [Required]


Mar, 1: Test set & background set release


Mar, 4: Test set predictions due


Mar, 15: System descriptions due


Apr, 1: Acceptance notification


Apr, 12: Camera-ready system descriptions


June 6–11: NAACL 2021 conference


 


Publications and workshop


Each participating team will have the opportunity to submit a system description which will be published as part of the shared task proceedings.


The 6th SMM4H Workshop, co-located at NAACL 2021. More details are available at https://healthlanguageprocessing.org/smm...

Área temática:Lingüística computacional, Lingüística de corpus
Comité científico

Olivier Bodenreider, US National Library of Medicine, USA


Kevin Cohen, University of Colorado School of Medicine, USA


Robert Leaman, US National Library of Medicine, USA


Diego Molla, Macquarie University, Australia


Zhiyong Lu, US National Library of Medicine, USA


Azadeh Nikfarjam, Apple, USA


Thierry Poibeau, French National Center for Scientific Research, France


Kirk Roberts, University of Texas Health Science Center at Houston, USA


Yutaka Sasaki, Toyota Technological Institute, Japan


H. Andrew Schwartz, Stony Brook University, USA


Nicolas Turenne, French National Institute for Agricultural Research, France


Karin Verspoor, University of Melbourne, Australia


Pierre Zweigenbaum, French National Center for Scientific Research, France

Comité organizador

Track Organizers


Martin Krallinger, Barcelona Supercomputing Center, Spain


Antonio Miranda-Escalada, Barcelona Supercomputing Center, Spain


Eulàlia Farré, Barcelona Supercomputing Center, Spain


Salvador Lima, Barcelona Supercomputing Center, Spain


 


SMM4H Organizers


Graciela Gonzalez-Hernandez, University of Pennsylvania, USA


Davy Weissenbacher, University of Pennsylvania, USA


Ari Z. Klein, University of Pennsylvania, USA


Karen O’Connor, University of Pennsylvania, USA


Abeed Sarker, Emory University, USA


Elena Tutubalina, Kazan Federal University, Russia


Zulfat Miftahutdinov, Kazan Federal University, Russia


Ilsear Alimova, Kazan Federal University, Russia


Martin Krallinger, Barcelona Supercomputing Center, Spain


Juan Banda, Georgia State University, USA

Lengua(s) oficial(es) del evento:

inglés

Remitente:Martin Krallinger
Institución: Barcelona Supercomputing center (BSC)
Correo-e: <krallinger.martingmail.com>
Fecha de publicación en Infoling:9 de febrero de 2021