Labeled entities from social media data related to avian influenza disease

This dataset is composed by spatial (e.g. location) and thematic (e.g. diseases, symptoms, virus) entities concerning avian influenza in social media (textual) data in English. It was created from three corpora: the first one includes 10 transcriptions of YouTube videos and 70 tweets manually annotated. The second corpus is composed by the same textual data but automatically annotated with Named Entity Recognition (NER) tools. These two corpora have been built to evaluate NER tools and apply them to a bigger corpus. The third corpus is composed of 100 YouTube transcriptions automatically annotated with NER tools. The aim of the annotation task is to recognize spatial information such as the names of the cities and epidemiological information such as the names of the diseases. An annotation guideline is provided in order to ensure a unified annotation and to help the annotators. This dataset can be used to train or evaluate Natural Language Processing (NLP) approaches such as specialized entity recognition.

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Bibliographic Details
Main Authors: Schaeffer, Camille, Interdonato, Roberto, Lancelot, Renaud, Roche, Mathieu, Teisseire, Maguelonne
Format: article biblioteca
Language:eng
Subjects:U10 - Informatique, mathématiques et statistiques, C30 - Documentation et information, L73 - Maladies des animaux, fouille de textes, médias sociaux, données spatiales, analyse de données, grippe aviaire, épidémiologie, http://aims.fao.org/aos/agrovoc/c_dca12b72, http://aims.fao.org/aos/agrovoc/c_8fbc05c3, http://aims.fao.org/aos/agrovoc/c_379bbe9f, http://aims.fao.org/aos/agrovoc/c_15962, http://aims.fao.org/aos/agrovoc/c_331337, http://aims.fao.org/aos/agrovoc/c_2615,
Online Access:http://agritrop.cirad.fr/601106/
http://agritrop.cirad.fr/601106/1/Camille_Schaeffer_DIB.pdf
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spelling dig-cirad-fr-6011062024-01-29T19:05:36Z http://agritrop.cirad.fr/601106/ http://agritrop.cirad.fr/601106/ Labeled entities from social media data related to avian influenza disease. Schaeffer Camille, Interdonato Roberto, Lancelot Renaud, Roche Mathieu, Teisseire Maguelonne. 2022. Data in Brief, 43:108317, 7 p.https://doi.org/10.1016/j.dib.2022.108317 <https://doi.org/10.1016/j.dib.2022.108317> Labeled entities from social media data related to avian influenza disease Schaeffer, Camille Interdonato, Roberto Lancelot, Renaud Roche, Mathieu Teisseire, Maguelonne eng 2022 Data in Brief U10 - Informatique, mathématiques et statistiques C30 - Documentation et information L73 - Maladies des animaux fouille de textes médias sociaux données spatiales analyse de données grippe aviaire épidémiologie http://aims.fao.org/aos/agrovoc/c_dca12b72 http://aims.fao.org/aos/agrovoc/c_8fbc05c3 http://aims.fao.org/aos/agrovoc/c_379bbe9f http://aims.fao.org/aos/agrovoc/c_15962 http://aims.fao.org/aos/agrovoc/c_331337 http://aims.fao.org/aos/agrovoc/c_2615 This dataset is composed by spatial (e.g. location) and thematic (e.g. diseases, symptoms, virus) entities concerning avian influenza in social media (textual) data in English. It was created from three corpora: the first one includes 10 transcriptions of YouTube videos and 70 tweets manually annotated. The second corpus is composed by the same textual data but automatically annotated with Named Entity Recognition (NER) tools. These two corpora have been built to evaluate NER tools and apply them to a bigger corpus. The third corpus is composed of 100 YouTube transcriptions automatically annotated with NER tools. The aim of the annotation task is to recognize spatial information such as the names of the cities and epidemiological information such as the names of the diseases. An annotation guideline is provided in order to ensure a unified annotation and to help the annotators. This dataset can be used to train or evaluate Natural Language Processing (NLP) approaches such as specialized entity recognition. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/601106/1/Camille_Schaeffer_DIB.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1016/j.dib.2022.108317 10.1016/j.dib.2022.108317 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.dib.2022.108317 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1016/j.dib.2022.108317 info:eu-repo/semantics/dataset/purl/https://doi.org/10.15454/GR5EFS
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
L73 - Maladies des animaux
fouille de textes
médias sociaux
données spatiales
analyse de données
grippe aviaire
épidémiologie
http://aims.fao.org/aos/agrovoc/c_dca12b72
http://aims.fao.org/aos/agrovoc/c_8fbc05c3
http://aims.fao.org/aos/agrovoc/c_379bbe9f
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_331337
http://aims.fao.org/aos/agrovoc/c_2615
U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
L73 - Maladies des animaux
fouille de textes
médias sociaux
données spatiales
analyse de données
grippe aviaire
épidémiologie
http://aims.fao.org/aos/agrovoc/c_dca12b72
http://aims.fao.org/aos/agrovoc/c_8fbc05c3
http://aims.fao.org/aos/agrovoc/c_379bbe9f
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_331337
http://aims.fao.org/aos/agrovoc/c_2615
spellingShingle U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
L73 - Maladies des animaux
fouille de textes
médias sociaux
données spatiales
analyse de données
grippe aviaire
épidémiologie
http://aims.fao.org/aos/agrovoc/c_dca12b72
http://aims.fao.org/aos/agrovoc/c_8fbc05c3
http://aims.fao.org/aos/agrovoc/c_379bbe9f
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_331337
http://aims.fao.org/aos/agrovoc/c_2615
U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
L73 - Maladies des animaux
fouille de textes
médias sociaux
données spatiales
analyse de données
grippe aviaire
épidémiologie
http://aims.fao.org/aos/agrovoc/c_dca12b72
http://aims.fao.org/aos/agrovoc/c_8fbc05c3
http://aims.fao.org/aos/agrovoc/c_379bbe9f
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_331337
http://aims.fao.org/aos/agrovoc/c_2615
Schaeffer, Camille
Interdonato, Roberto
Lancelot, Renaud
Roche, Mathieu
Teisseire, Maguelonne
Labeled entities from social media data related to avian influenza disease
description This dataset is composed by spatial (e.g. location) and thematic (e.g. diseases, symptoms, virus) entities concerning avian influenza in social media (textual) data in English. It was created from three corpora: the first one includes 10 transcriptions of YouTube videos and 70 tweets manually annotated. The second corpus is composed by the same textual data but automatically annotated with Named Entity Recognition (NER) tools. These two corpora have been built to evaluate NER tools and apply them to a bigger corpus. The third corpus is composed of 100 YouTube transcriptions automatically annotated with NER tools. The aim of the annotation task is to recognize spatial information such as the names of the cities and epidemiological information such as the names of the diseases. An annotation guideline is provided in order to ensure a unified annotation and to help the annotators. This dataset can be used to train or evaluate Natural Language Processing (NLP) approaches such as specialized entity recognition.
format article
topic_facet U10 - Informatique, mathématiques et statistiques
C30 - Documentation et information
L73 - Maladies des animaux
fouille de textes
médias sociaux
données spatiales
analyse de données
grippe aviaire
épidémiologie
http://aims.fao.org/aos/agrovoc/c_dca12b72
http://aims.fao.org/aos/agrovoc/c_8fbc05c3
http://aims.fao.org/aos/agrovoc/c_379bbe9f
http://aims.fao.org/aos/agrovoc/c_15962
http://aims.fao.org/aos/agrovoc/c_331337
http://aims.fao.org/aos/agrovoc/c_2615
author Schaeffer, Camille
Interdonato, Roberto
Lancelot, Renaud
Roche, Mathieu
Teisseire, Maguelonne
author_facet Schaeffer, Camille
Interdonato, Roberto
Lancelot, Renaud
Roche, Mathieu
Teisseire, Maguelonne
author_sort Schaeffer, Camille
title Labeled entities from social media data related to avian influenza disease
title_short Labeled entities from social media data related to avian influenza disease
title_full Labeled entities from social media data related to avian influenza disease
title_fullStr Labeled entities from social media data related to avian influenza disease
title_full_unstemmed Labeled entities from social media data related to avian influenza disease
title_sort labeled entities from social media data related to avian influenza disease
url http://agritrop.cirad.fr/601106/
http://agritrop.cirad.fr/601106/1/Camille_Schaeffer_DIB.pdf
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AT lancelotrenaud labeledentitiesfromsocialmediadatarelatedtoavianinfluenzadisease
AT rochemathieu labeledentitiesfromsocialmediadatarelatedtoavianinfluenzadisease
AT teisseiremaguelonne labeledentitiesfromsocialmediadatarelatedtoavianinfluenzadisease
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