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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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AI4PROFHEALTH Profession and occupations gazetteer (ProfNER & MEDDOPROF - occupations, professions and working status terms with their associated codes)

Authors: Asensio, Alejandro; Miranda-Escalada, Antonio; Aguero, Marvin; Krallinger, Martin;

AI4PROFHEALTH Profession and occupations gazetteer (ProfNER & MEDDOPROF - occupations, professions and working status terms with their associated codes)

Abstract

Gazetteer of occupations extracted from a set of terminologies (DeCS, ESCO, SnomedCT and WordNet). In addition, we include in the gazetteer a list of occupations detected by Stanford CoreNLP in a large collection of social media profiles. For every term, we include its lemma. The lemma was extracted using the PlanTL Med_Tagger: https://github.com/PlanTL-SANIDAD/SPACCC_POS-TAGGER Please, cite: Miranda-Escalada, A., Farré-Maduell, E., Lima-López, S., Gascó, L., Briva-Iglesias, V., Agüero-Torales, M., & Krallinger, M. (2021, June). The profner shared task on automatic recognition of occupation mentions in social media: systems, evaluation, guidelines, embeddings and corpora. In Proceedings of the Sixth Social Media Mining for Health (# SMM4H) Workshop and Shared Task (pp. 13-20). @inproceedings{miranda2021profner, title={The profner shared task on automatic recognition of occupation mentions in social media: systems, evaluation, guidelines, embeddings and corpora}, author={Miranda-Escalada, Antonio and Farr{\'e}-Maduell, Eul{\`a}lia and Lima-L{\'o}pez, Salvador and Gasc{\'o}, Luis and Briva-Iglesias, Vicent and Ag{\"u}ero-Torales, Marvin and Krallinger, Martin}, booktitle={Proceedings of the Sixth Social Media Mining for Health (\# SMM4H) Workshop and Shared Task}, pages={13--20}, year={2021} } For further information, please visit https://temu.bsc.es/smm4h-spanish/ or email us at encargo-pln-life@bsc.es Resources: Web Gold Standard Annotation guidelines (in Spanish) Annotation guidelines (in English) FastText COVID-19 Twitter embeddings Conference Proceedings

Funded by the Plan de Impulso de las Tecnologías del Lenguaje (Plan TL).

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Keywords

ProfNER, occupations, gazetteer

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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