Mental-Health: An NLP-Based System for Detecting Depression Levels through User Comments on Twitter (X)

Rafael Salas-Zárate; Giner Alor-Hernández; Mario Andrés Paredes-Valverde; María del Pilar Salas-Zárate; Maritza Bustos-López; José Luis Sánchez-Cervantes

doi:10.3390/math12131926

journal article Open Access Jun 21, 2024

Mental-Health: An NLP-Based System for Detecting Depression Levels through User Comments on Twitter (X)

Rafael Salas-Zárate Giner Alor-Hernández

Mario Andrés Paredes-Valverde

María del Pilar Salas-Zárate

Maritza Bustos-López José Luis Sánchez-Cervantes

Mathematics Vol. 12 No. 13 pp. 1926 · MDPI AG

View at Publisher Save 10.3390/math12131926

Abstract

The early detection of depression in a person is of great help to medical specialists since it allows for better treatment of the condition. Social networks are a promising data source for identifying individuals who are at risk for this mental disease, facilitating timely intervention and thereby improving public health. In this frame of reference, we propose an NLP-based system called Mental-Health for detecting users’ depression levels through comments on X. Mental-Health is supported by a model comprising four stages: data extraction, preprocessing, emotion detection, and depression diagnosis. Using a natural language processing tool, the system correlates emotions detected in users’ posts on X with the symptoms of depression and provides specialists with the depression levels of the patients. By using Mental-Health, we described a case study involving real patients, and the evaluation process was carried out by comparing the results obtained using Mental-Health with those obtained through the application of the PHQ-9 questionnaire. The system identifies moderately severe and moderate depression levels with good precision and recall, allowing us to infer the model’s good performance and confirm that it is a promising option for mental health support.

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Details

Published: Jun 21, 2024
Vol/Issue: 12(13)
Pages: 1926
License: View

Authors

R

Rafael Salas-Zárate

Tecnológico Nacional de México/I. T. Zitácuaro, Av. Tecnológico No. 186, Zitácuaro 61534, Michoacán, Mexico; Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 No. 852, Col. E. Zapata, Orizaba 94320, Veracruz, Mexico

G

Giner Alor-Hernández

Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 No. 852, Col. E. Zapata, Orizaba 94320, Veracruz, Mexico

M

Mario Andrés Paredes-Valverde

Tecnológico Nacional de México/I.T.S. Teziutlán, Fracción I y II S/N, Aire Libre, Teziutlán 73960, Puebla, Mexico

M

María del Pilar Salas-Zárate

Tecnológico Nacional de México/I.T.S. Teziutlán, Fracción I y II S/N, Aire Libre, Teziutlán 73960, Puebla, Mexico

M

Maritza Bustos-López

Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 No. 852, Col. E. Zapata, Orizaba 94320, Veracruz, Mexico

J

José Luis Sánchez-Cervantes

Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 No. 852, Col. E. Zapata, Orizaba 94320, Veracruz, Mexico

Cite This Article

Rafael Salas-Zárate, Giner Alor-Hernández, Mario Andrés Paredes-Valverde, et al. (2024). Mental-Health: An NLP-Based System for Detecting Depression Levels through User Comments on Twitter (X). Mathematics, 12(13), 1926. https://doi.org/10.3390/math12131926

Mental-Health: An NLP-Based System for Detecting Depression Levels through User Comments on Twitter (X)

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