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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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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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 |
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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 |
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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 |
work_keys_str_mv |
AT schaeffercamille labeledentitiesfromsocialmediadatarelatedtoavianinfluenzadisease AT interdonatoroberto labeledentitiesfromsocialmediadatarelatedtoavianinfluenzadisease AT lancelotrenaud labeledentitiesfromsocialmediadatarelatedtoavianinfluenzadisease AT rochemathieu labeledentitiesfromsocialmediadatarelatedtoavianinfluenzadisease AT teisseiremaguelonne labeledentitiesfromsocialmediadatarelatedtoavianinfluenzadisease |
_version_ |
1792500359050035200 |