Using Text Classification to Estimate the Depression Level of Reddit Users

Psychologists have used tests and carefully designed survey questions, such as Beck’s Depression Inventory (BDI), to identify the presence of depression and to assess its severity level. On the other hand, methods for automatic depression detection have gained increasing interest since all the infor...

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Detalles Bibliográficos
Autores principales: Burdisso, Sergio G., Errecalde, Marcelo Luis, Montes y Gómez, Manuel
Formato: Articulo
Lenguaje:Inglés
Publicado: 2021
Materias:
Ciencias Informáticas
Beck’s Depression Inventory
Clasificación de textos,
CLEF eRisk 2019
Depression Level Estimation
Estimación del nivel de depresión
SS3
Text Classification
Inventario de Depresión de Beck
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/118067
https://journal.info.unlp.edu.ar/JCST/article/view/1352
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-118067
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Beck’s Depression Inventory
Clasificación de textos,
CLEF eRisk 2019
Depression Level Estimation
Estimación del nivel de depresión
SS3
Text Classification
Inventario de Depresión de Beck
spellingShingle Ciencias Informáticas
Beck’s Depression Inventory
Clasificación de textos,
CLEF eRisk 2019
Depression Level Estimation
Estimación del nivel de depresión
SS3
Text Classification
Inventario de Depresión de Beck
Burdisso, Sergio G.
Errecalde, Marcelo Luis
Montes y Gómez, Manuel
Using Text Classification to Estimate the Depression Level of Reddit Users
topic_facet Ciencias Informáticas
Beck’s Depression Inventory
Clasificación de textos,
CLEF eRisk 2019
Depression Level Estimation
Estimación del nivel de depresión
SS3
Text Classification
Inventario de Depresión de Beck
description Psychologists have used tests and carefully designed survey questions, such as Beck’s Depression Inventory (BDI), to identify the presence of depression and to assess its severity level. On the other hand, methods for automatic depression detection have gained increasing interest since all the information available in social media, such as Twitter and Facebook, enables novel approaches based on language use. More precisely, these methods have focused on learning to detect depressive users through their language usage. However, little effort has been put into going beyond mere detection, towards estimating users’ actual clinical depression level. The present study is a first step towards that direction: we try to develop a model able to estimate Reddit’s users’ clinical depression level by filling in the BDI depression questionnaire on behalf of each user. To carry out his task, the model answers all 21 questions of the questionnaire using the confidence value outputted by a binary text classifier trained to detect depressed users on Reddit. Our proposal was publicly tested in the CLEF’s eRisk 2019 lab obtaining the best and second-best performance among the other 13 submitted models.
format Articulo
Articulo
author Burdisso, Sergio G.
Errecalde, Marcelo Luis
Montes y Gómez, Manuel
author_facet Burdisso, Sergio G.
Errecalde, Marcelo Luis
Montes y Gómez, Manuel
author_sort Burdisso, Sergio G.
title Using Text Classification to Estimate the Depression Level of Reddit Users
title_short Using Text Classification to Estimate the Depression Level of Reddit Users
title_full Using Text Classification to Estimate the Depression Level of Reddit Users
title_fullStr Using Text Classification to Estimate the Depression Level of Reddit Users
title_full_unstemmed Using Text Classification to Estimate the Depression Level of Reddit Users
title_sort using text classification to estimate the depression level of reddit users
publishDate 2021
url http://sedici.unlp.edu.ar/handle/10915/118067
https://journal.info.unlp.edu.ar/JCST/article/view/1352
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