Early Risk Prediction of Mental Health Disorders
The monitoring of social media use and postings to discern users' mental health is not a novel application of Information Retrieval, Text Mining, and Natural Language Processing. Yet, the evaluation of the proposed solutions has only recently started to be properly addressed. The eRisk project aims at stimulating research on such topic by providing an experimental framework that enables the proper development and testing of tools that not only can detect signs of failing mental health, but that can also track such signs over time and flag a warning when they become serious. This book provides the context in which this project was developed and presents the best results achieved so far. This chapter introduces the book and gives an overview of its content.
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Publication: Book
1663588123800
September 19, 2022
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The monitoring of social media use and postings to discern users' mental health is not a novel application of Information Retrieval, Text Mining, and Natural Language Processing. Yet, the evaluation of the proposed solutions has only recently started to be properly addressed. The eRisk project aims at stimulating research on such topic by providing an experimental framework that enables the proper development and testing of tools that not only can detect signs of failing mental health, but that can also track such signs over time and flag a warning when they become serious. This book provides the context in which this project was developed and presents the best results achieved so far. This chapter introduces the book and gives an overview of its content. - Fabio Crestani, David E. Losada y Javier Parapar - 10.1007/978-3-031-04431-1_1 - 978-3-031-04430-4
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