Examining the relationship between COVID-19 and suicide in media coverage through Natural Language Processing analysis
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). To study how suicide is depicted in new...
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| Veröffentlicht in: | The European journal of psychiatry Jg. 38; H. 1; S. 100227 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier España, S.L.U
01.01.2024
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| ISSN: | 0213-6163, 2340-4469 |
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| Abstract | 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).
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.
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”.
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. |
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| AbstractList | 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).
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.
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”.
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. AbstractBackground and objectivesSuicide 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). MethodsTo 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. ResultsA 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”. ConclusionsOur 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. |
| ArticleNumber | 100227 |
| Author | Palomar-Ciria, Nora Baca-García, Enrique Gutiérrez-Alonso, Carlos Bello, Hugo J. Lozano, Celia |
| Author_xml | – sequence: 1 givenname: Hugo J. surname: Bello fullname: Bello, Hugo J. email: hugojose.bello@uva.es organization: Department of Applied Mathematics, Universidad de Valladolid, Soria, Spain – sequence: 2 givenname: Nora orcidid: 0000-0002-2293-3106 surname: Palomar-Ciria fullname: Palomar-Ciria, Nora organization: Servicio de Psiquiatría, Complejo Asistencial Universitario de Soria, Soria, Spain – sequence: 3 givenname: Celia surname: Lozano fullname: Lozano, Celia organization: Department of Data & Analytics, Bosonit, Logroño (La Rioja), Spain – sequence: 4 givenname: Carlos surname: Gutiérrez-Alonso fullname: Gutiérrez-Alonso, Carlos organization: Department of Artificial Intelligence, Sermes CRO, Madrid, Spain – sequence: 5 givenname: Enrique surname: Baca-García fullname: Baca-García, Enrique organization: Department of Psychiatry, Hospital Universitario Fundación Jiménez Díaz, Madrid, Spain |
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| Keywords | Big data Suicide Public health Topic classification Machine learning |
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| SubjectTerms | Big data Machine learning Psychiatric/Mental Health Public health Suicide Topic classification |
| Title | Examining the relationship between COVID-19 and suicide in media coverage through Natural Language Processing analysis |
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