A profile-based sentiment-aware approach for depression detection in social media

Abstract Depression is a severe mental health problem. Due to its relevance, the development of computational tools for its detection has attracted increasing attention in recent years. In this context, several research works have addressed the problem using word-based approaches (e.g., a bag of wor...

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Autores principales:	José de Jesús Titla-Tlatelpa, Rosa María Ortega-Mendoza, Manuel Montes-y-Gómez, Luis Villaseñor-Pineda
Formato:	article
Lenguaje:	EN
Publicado:	SpringerOpen 2021
Materias:	Depression detection Author profiling Sentiment analysis Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/f436163ae1b54c9f9d1cc93b3b6f2151
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id	oai:doaj.org-article:f436163ae1b54c9f9d1cc93b3b6f2151
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spelling	oai:doaj.org-article:f436163ae1b54c9f9d1cc93b3b6f21512021-11-08T11:17:12ZA profile-based sentiment-aware approach for depression detection in social media10.1140/epjds/s13688-021-00309-32193-1127https://doaj.org/article/f436163ae1b54c9f9d1cc93b3b6f21512021-11-01T00:00:00Zhttps://doi.org/10.1140/epjds/s13688-021-00309-3https://doaj.org/toc/2193-1127Abstract Depression is a severe mental health problem. Due to its relevance, the development of computational tools for its detection has attracted increasing attention in recent years. In this context, several research works have addressed the problem using word-based approaches (e.g., a bag of words). This type of representation has shown to be useful, indicating that words act as linguistic markers of depression. However, we believe that in addition to words, their contexts contain implicitly valuable information that could be inferred and exploited to enhance the detection of signs of depression. Specifically, we explore the use of user’s characteristics and the expressed sentiments in the messages as context insights. The main idea is that the words’ discriminative value depends on the characteristics of the person who is writing and on the polarity of the messages where they occur. Hence, this paper introduces a new approach based on specializing the framework of classification to profiles of users (e.g., males or women) and considering the sentiments expressed in the messages through a new text representation that captures their polarity (e.g., positive or negative). The proposed approach was evaluated on benchmark datasets from social media; the results achieved are encouraging, since they outperform those of state-of-the-art corresponding to computationally more expensive methods.José de Jesús Titla-TlatelpaRosa María Ortega-MendozaManuel Montes-y-GómezLuis Villaseñor-PinedaSpringerOpenarticleDepression detectionAuthor profilingSentiment analysisComputer applications to medicine. Medical informaticsR858-859.7ENEPJ Data Science, Vol 10, Iss 1, Pp 1-18 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Depression detection Author profiling Sentiment analysis Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Depression detection Author profiling Sentiment analysis Computer applications to medicine. Medical informatics R858-859.7 José de Jesús Titla-Tlatelpa Rosa María Ortega-Mendoza Manuel Montes-y-Gómez Luis Villaseñor-Pineda A profile-based sentiment-aware approach for depression detection in social media
description	Abstract Depression is a severe mental health problem. Due to its relevance, the development of computational tools for its detection has attracted increasing attention in recent years. In this context, several research works have addressed the problem using word-based approaches (e.g., a bag of words). This type of representation has shown to be useful, indicating that words act as linguistic markers of depression. However, we believe that in addition to words, their contexts contain implicitly valuable information that could be inferred and exploited to enhance the detection of signs of depression. Specifically, we explore the use of user’s characteristics and the expressed sentiments in the messages as context insights. The main idea is that the words’ discriminative value depends on the characteristics of the person who is writing and on the polarity of the messages where they occur. Hence, this paper introduces a new approach based on specializing the framework of classification to profiles of users (e.g., males or women) and considering the sentiments expressed in the messages through a new text representation that captures their polarity (e.g., positive or negative). The proposed approach was evaluated on benchmark datasets from social media; the results achieved are encouraging, since they outperform those of state-of-the-art corresponding to computationally more expensive methods.
format	article
author	José de Jesús Titla-Tlatelpa Rosa María Ortega-Mendoza Manuel Montes-y-Gómez Luis Villaseñor-Pineda
author_facet	José de Jesús Titla-Tlatelpa Rosa María Ortega-Mendoza Manuel Montes-y-Gómez Luis Villaseñor-Pineda
author_sort	José de Jesús Titla-Tlatelpa
title	A profile-based sentiment-aware approach for depression detection in social media
title_short	A profile-based sentiment-aware approach for depression detection in social media
title_full	A profile-based sentiment-aware approach for depression detection in social media
title_fullStr	A profile-based sentiment-aware approach for depression detection in social media
title_full_unstemmed	A profile-based sentiment-aware approach for depression detection in social media
title_sort	profile-based sentiment-aware approach for depression detection in social media
publisher	SpringerOpen
publishDate	2021
url	https://doaj.org/article/f436163ae1b54c9f9d1cc93b3b6f2151
work_keys_str_mv	AT josedejesustitlatlatelpa aprofilebasedsentimentawareapproachfordepressiondetectioninsocialmedia AT rosamariaortegamendoza aprofilebasedsentimentawareapproachfordepressiondetectioninsocialmedia AT manuelmontesygomez aprofilebasedsentimentawareapproachfordepressiondetectioninsocialmedia AT luisvillasenorpineda aprofilebasedsentimentawareapproachfordepressiondetectioninsocialmedia AT josedejesustitlatlatelpa profilebasedsentimentawareapproachfordepressiondetectioninsocialmedia AT rosamariaortegamendoza profilebasedsentimentawareapproachfordepressiondetectioninsocialmedia AT manuelmontesygomez profilebasedsentimentawareapproachfordepressiondetectioninsocialmedia AT luisvillasenorpineda profilebasedsentimentawareapproachfordepressiondetectioninsocialmedia
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A profile-based sentiment-aware approach for depression detection in social media

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