PDF(Pubmed)
Abstract：
UNASSIGNED: 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.
UNASSIGNED: Complete written content of N = 192 users, including n = 48 identified as potential suicide completers/highest-risk users (HRUs), on the pro-choice suicide forum, Sanctioned Suicide, was modeled using a combination of lexicon-based topic modeling (EMPATH) and exploratory network analysis techniques to characterize and highlight prominent aspects of censorship-free suicidal discourse.
UNASSIGNED: Modeling of over 2 million tokens across 37,136 forum posts found higher frequency of positive emotion and optimism among HRUs, emphasis on methods seeking and sharing behaviors, prominence of previously undocumented jargon, and semantics related to loneliness and life adversity.
UNASSIGNED: This natural language processing (NLP)- and network-driven exposé of online STB subculture uncovered trends that deserve further attention within suicidology as they may be able to bolster detection, intervention, and prevention of suicidal outcomes and exposures.
UNASSIGNED: Complete written content of N = 192 users, including n = 48 identified as potential suicide completers/highest-risk users (HRUs), on the pro-choice suicide forum, Sanctioned Suicide, was modeled using a combination of lexicon-based topic modeling (EMPATH) and exploratory network analysis techniques to characterize and highlight prominent aspects of censorship-free suicidal discourse.
UNASSIGNED: Modeling of over 2 million tokens across 37,136 forum posts found higher frequency of positive emotion and optimism among HRUs, emphasis on methods seeking and sharing behaviors, prominence of previously undocumented jargon, and semantics related to loneliness and life adversity.
UNASSIGNED: This natural language processing (NLP)- and network-driven exposé of online STB subculture uncovered trends that deserve further attention within suicidology as they may be able to bolster detection, intervention, and prevention of suicidal outcomes and exposures.
摘要：
■自杀思想和行为（STB）的社会吸引力和污名化性质使其特别容易受到大多数现代数字通信平台的审查。技术与日常生活的无处不在的集成为利用前所未有的大量数据来研究STB提供了宝贵的机会，然而，主流在线社区中研究审查制度的复杂病因和后果使STB表现不完整。在减轻对责备的恐惧的环境中针对自杀用户的在线书面内容的分析可以提供对STB表达的现代趋势和信号的新颖见解。
■N=192个用户的完整书面内容，包括被确定为潜在自杀完成者/最高风险用户(HRU)的n=48，在支持选择自杀论坛上，制裁自杀,使用基于词典的主题建模（EMPATH）和探索性网络分析技术进行建模，以表征和突出无审查自杀话语的突出方面。
■在37,136个论坛帖子中对超过200万个令牌进行建模，发现HRU中积极情绪和乐观情绪的频率更高，强调寻求和分享行为的方法，突出以前没有记载的行话，以及与孤独和生活逆境有关的语义。
■这种自然语言处理（NLP）和网络驱动的在线STB亚文化暴露揭示了趋势，值得在自杀学中进一步关注，因为它们可能能够支持检测，干预，以及预防自杀结果和暴露。
■N=192个用户的完整书面内容，包括被确定为潜在自杀完成者/最高风险用户(HRU)的n=48，在支持选择自杀论坛上，制裁自杀,使用基于词典的主题建模（EMPATH）和探索性网络分析技术进行建模，以表征和突出无审查自杀话语的突出方面。
■在37,136个论坛帖子中对超过200万个令牌进行建模，发现HRU中积极情绪和乐观情绪的频率更高，强调寻求和分享行为的方法，突出以前没有记载的行话，以及与孤独和生活逆境有关的语义。
■这种自然语言处理（NLP）和网络驱动的在线STB亚文化暴露揭示了趋势，值得在自杀学中进一步关注，因为它们可能能够支持检测，干预，以及预防自杀结果和暴露。
