Examining the relationship between COVID-19 and suicide in media coverage through Natural Language Processing analysis

Bello, Hugo J.; Palomar-Ciria, Nora; Lozano, Celia; Gutiérrez-Alonso, Carlos; Baca-García, Enrique

doi:10.1016/j.ejpsy.2023.100227

ISSN: 0213-6163

The European Journal of Psychiatry is a quarterly publication founded in 1986 and directed by Professor A. Seva until his death in 2004. The journal is indexed in different bibliographic data bases, including the Social Sciences Citation Index. It is supported by the Spanish Society of Psychiatry and Mental Health, has been open to contributions from all over the world, and also has North American and Asian-Pacific co- editors. A new stage of development of the journal has started in 2017. A new Editorial Board has been appointed and an advanced on-line editorial system has been implemented. Our new publishing partners will help to assure that our valuable research gets broadly disseminated, providing a more accessible entry into our contribution. The overriding criteria for publication are originality, a high scientific quality and interest to a wide audience of those concerned with all aspects of mental illness. The scope is broad and the journal is committed to present new developments in the full spectrum of issues related to psychiatry and mental health, in areas linked to biological, psychological and social sciences. It will include basic studies and the growing application of clinical laboratory techniques in psychiatry. The European Journal of Psychiatry is determined to place particular emphasis on clinical issues related to a personalised medicine, including prevention and early intervention. All original papers will be refereed by independent experts in the field. Review articles and monographs designed to bring the reader up to date with research in the area will be a feature of the journal. There is a Book Review section and correspondence to the editor will be considered for publication. The journal will be of interest to psychiatrists, psychologists, social scientists, nurses and others engaged in mental health professions, together with basic neurobiological researchers.

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Social Sciences Citation Index. Behavioral Measurement Data Base Services (BMDS). Biosciences Information Service (BIOSIS). Current Contents / Social Behavioral Sciences. e-psyche LLC. Excerpta Medica (EMBASE). Índice Bibliográfico Español en Ciencias de la Salud (IBECS). ISOC. Mental Health Abstracts DataBase. NISC Family Studies Databases. PsycAlert. Psychological Abstracts (PA). PsycINFO. Social Planning Policy and Development (SODOPA). Sociological Abstracts (SA). SCOPUS

Table 1. ML metrics of the models trained for news classification. The precision is the ratio tp / (tp + fp) where tp is the number of true positives and fp the number of false positives. The recall is the ratio tp / (tp + fn) where fn is the number of false negatives. The F1 score can be interpreted as a harmonic mean of the precision and recall, where an F1 score reaches its best value at 1 and worst score at 0.

Abstract

Background and objectives

Suicide is a major public health concern, media can influence its awareness, contagion, and prevention. In this study, we evaluated the relationship between the COVID-19 pandemic and suicide in media coverage through Natural Language Processing analysis (NPL).

Methods

To study how suicide is depicted in news media, Artificial Intelligence and Big Data techniques were used to analyze news and tweets, to extract or classify the topic to which they belonged.

Results

A granger causality analysis showed with significant p-value that an increase in covid news at the beginning of the pandemic explains a later rise in suicide-related news. An analysis based on correlation and structural causal models show a strong relationship between the appearance of subjects “health” and “covid”, and also between “covid” and “suicide”.

Conclusions

Our analysis also uncovers that the inclusion of suicide-related news in the category health has grown since the outbreak of the pandemic. The COVID-19 pandemic has posed an inflection point in the way suicide-related news are reported. Our study found that the increased media attention on suicide during the COVID-19 pandemic may indicate rising social awareness of suicide and mental health, which could lead to the development of new prevention tools.

Keywords:

Suicide

Public health

Big data

Topic classification

Machine learning

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