Topic modelling online depression forums: beyond narratives of self-objectification and self-blaming.
J Ment Health
; 32(2): 386-395, 2023 Apr.
Article
em En
| MEDLINE
| ID: mdl-34582309
BACKGROUND: Depression raises a double challenge: besides the negative mood and the intrusive thoughts, the relation to the self also becomes difficult. Online forums are analysed as communicative platforms enabling the interactive reconstruction of the self. AIMS: The discourses of online depression forums are explored. Firstly, narrative patterns are identified according to their thematic focus (e.g. dysfunctional body, challenges of intimacy) and discursive logic (e.g. information exchange, support). Secondly, narratives are analysed in order to describe various ways of grounding a depressed self. METHODS: â¼70.000 depression-related posts from the biggest English-speaking online forums (e.g. www.reddit.com/r/depression, www.healthunlocked.com) were analysed. Quantitative (LDA topic modelling) and qualitative (deep reading) approaches were used simultaneously to determine the optimal number of topics and their interpretation. RESULTS: 13 topics were identified and interpreted according to their content and communicative function. Based on the inter-topic distances four clusters were identified (medicalized, intimacy-oriented, critical and uninhabitable self-narratives). CONCLUSIONS: The clusters of the 13 topics highlight various ways of narrating depression and the depressed self. Based on a comparison with a systematic review of mental illness recovery narratives, depression forums cover most narrative genres and emotional tones, thus create a unique opportunity for integrating the depressing experiences in the self.
Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Depressão
/
Transtornos Mentais
Tipo de estudo:
Qualitative_research
/
Systematic_reviews
Limite:
Humans
Idioma:
En
Revista:
J Ment Health
Assunto da revista:
PSICOLOGIA
/
PSIQUIATRIA
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Hungria