The hidden depths of suicidal discourse: Network analysis and natural language processing unmask uncensored expression.

ABSTRACT:

Background

The socially unattractive and stigmatizing nature of suicidal thought and behavior (STB) makes it especially susceptible to censorship across most modern digital communication platforms. The ubiquitous integration of technology with day-to-day life has presented an invaluable opportunity to leverage unprecedented amounts of data to study STB, yet the complex etiologies and consequences of censorship for research within mainstream online communities render an incomplete picture of STB manifestation. Analyses targeting online written content of suicidal users in environments where fear of reproach is mitigated may provide novel insight into modern trends and signals of STB expression.

Methods

Complete written content of N = 192 users, including n = 48

SUBMITTER: Lekkas D 

PROVIDER: S-EPMC10623973 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature