Suicide is a major global public health concern, especially among young people. Given that digital surroundings are progressively influencing communication patterns, young people frequently communicate their feelings online, including suicidal thoughts. By promptly drawing attention to these posts, a crucial preventive measure could be taken. A scoping review guided by the research question “What is the current state of the art in detecting suicidal ideation in online posts?” following PRISMA guidelines. Out of the 1584 articles identified, only 48 met the inclusion criteria. The majority of articles were related to posts written in English on Reddit and Twitter. The main aim of the studies were interpretative (aim to explore how suicidal ideation is expressed in online environments) or predictive (aim to identify posts that may indicate suicidal ideation) and most of the posts were analyzed using artificial intelligence rather than traditional methods. Some, however, used mixed methods. Despite the potential of AI for rapidly processing and annotating suicidal notes, several hurdles remain, especially ethically obtained data sets and limited cross-cultural portability of models. Furthermore, current AI systems fail to interpret metaphors, irony, or context-specific meaning underscoring the requirement for hybrid models combining machine speed with human judgment.
Trentarossi et al. (2025) studied this question.