Modern Standard Arabic mood changing and depression dataset

This paper presents Modern Standard Arabic data for the automatic estimation of the risk of depression for online personas based on their daily Arabic tweets. The data were collected from 1-1-2020 to 1-1-2021 using automatically collected samples of depression and non-depression tweets. The data con...

Descripción completa

Detalles Bibliográficos
Autores principales: Maghraby, Ashwag, Ali, Hosnia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8902608/
https://www.ncbi.nlm.nih.gov/pubmed/35274028
http://dx.doi.org/10.1016/j.dib.2022.107999
_version_ 1784664624659955712
author Maghraby, Ashwag
Ali, Hosnia
author_facet Maghraby, Ashwag
Ali, Hosnia
author_sort Maghraby, Ashwag
collection PubMed
description This paper presents Modern Standard Arabic data for the automatic estimation of the risk of depression for online personas based on their daily Arabic tweets. The data were collected from 1-1-2020 to 1-1-2021 using automatically collected samples of depression and non-depression tweets. The data contain 1229 records. These data can be used to develop machine-learning tools to identify the risk of an individual being depressed and to build recommender systems that monitor depression.
format Online
Article
Text
id pubmed-8902608
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-89026082022-03-09 Modern Standard Arabic mood changing and depression dataset Maghraby, Ashwag Ali, Hosnia Data Brief Data Article This paper presents Modern Standard Arabic data for the automatic estimation of the risk of depression for online personas based on their daily Arabic tweets. The data were collected from 1-1-2020 to 1-1-2021 using automatically collected samples of depression and non-depression tweets. The data contain 1229 records. These data can be used to develop machine-learning tools to identify the risk of an individual being depressed and to build recommender systems that monitor depression. Elsevier 2022-03-01 /pmc/articles/PMC8902608/ /pubmed/35274028 http://dx.doi.org/10.1016/j.dib.2022.107999 Text en © 2022 The Author(s). Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Maghraby, Ashwag
Ali, Hosnia
Modern Standard Arabic mood changing and depression dataset
title Modern Standard Arabic mood changing and depression dataset
title_full Modern Standard Arabic mood changing and depression dataset
title_fullStr Modern Standard Arabic mood changing and depression dataset
title_full_unstemmed Modern Standard Arabic mood changing and depression dataset
title_short Modern Standard Arabic mood changing and depression dataset
title_sort modern standard arabic mood changing and depression dataset
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8902608/
https://www.ncbi.nlm.nih.gov/pubmed/35274028
http://dx.doi.org/10.1016/j.dib.2022.107999
work_keys_str_mv AT maghrabyashwag modernstandardarabicmoodchanginganddepressiondataset
AT alihosnia modernstandardarabicmoodchanginganddepressiondataset

Ejemplares similares