A Big Data Platform for Real Time Analysis of Signs of Depression in Social Media
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Título: | A Big Data Platform for Real Time Analysis of Signs of Depression in Social Media |
Autor/a: | Martínez Castaño, Rodrigo Pichel Campos, Juan Carlos Losada Carril, David Enrique |
Centro/Departamento: | Universidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías da Información Universidade de Santiago de Compostela. Departamento de Electrónica e Computación |
Palabras chave: | Social Media | Text mining | Depression | Public health surveillance | Stream processing | Real-time processing | |
Data: | 2020 |
Editor: | MDPI |
Cita bibliográfica: | Martínez-Castaño, R.; Pichel, J.C.; Losada , D.E. A Big Data Platform for Real Time Analysis of Signs of Depression in Social Media. Int. J. Environ. Res. Public Health 2020, 17, 4752 |
Resumo: | In this paper we propose a scalable platform for real-time processing of Social Media data. The platform ingests huge amounts of contents, such as Social Media posts or comments, and can support Public Health surveillance tasks. The processing and analytical needs of multiple screening tasks can easily be handled by incorporating user-defined execution graphs. The design is modular and supports different processing elements, such as crawlers to extract relevant contents or classifiers to categorise Social Media. We describe here an implementation of a use case built on the platform that monitors Social Media users and detects early signs of depression |
Versión do editor: | https://doi.org/10.3390/ijerph17134752 |
URI: | http://hdl.handle.net/10347/23770 |
DOI: | 10.3390/ijerph17134752 |
E-ISSN: | 1660-4601 |
Dereitos: | © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/) Atribución 4.0 Internacional |
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- CiTIUS-Artigos [192]
- EC-Artigos [176]
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