| Literature DB >> 31437883 |
Ashwin Karthik Ambalavan1, Bilel Moulahi2, Jérome Azé3, Sandra Bringay3,4.
Abstract
Suicide is a growing public health concern in online communities. In this paper, we analyze online communications on the topic of suicide in the social networking platform, Reddit. We combine lexical text characteristics with semantic information to identify comments with features of suicide attempts and methods. Then, we develop a set of machine learning methods to automatically extract suicide methods and classify the user comments. Our classification methods performance varied between suicide experiences, with F1-scores up to 0.92 for "drugs" and greater than 0.82 for "hanging" and "other methods". Our exploratory analysis reveals that the most frequent reported suicide methods are drug overdose, hanging, and wrist-cutting.Entities:
Keywords: Natural Language Processing; Social Media; Suicide; attempted
Mesh:
Year: 2019 PMID: 31437883 DOI: 10.3233/SHTI190181
Source DB: PubMed Journal: Stud Health Technol Inform ISSN: 0926-9630