کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6856573 | 1437965 | 2018 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Online suicide prevention through optimised text classification
ترجمه فارسی عنوان
پیشگیری از خودکشی آنلاین از طریق طبقه بندی متن بهینه سازی شده
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کلمات کلیدی
پیشگیری از خودکشی، رسانه های اجتماعی، طبقه بندی متن، فراگیری ماشین، انتخاب ویژگی، بهینه سازی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Online communication platforms are increasingly used to express suicidal thoughts. There is considerable interest in monitoring such messages, both for population-wide and individual prevention purposes, and to inform suicide research and policy. Online information overload prohibits manual detection, which is why keyword search methods are typically used. However, these are imprecise and unable to handle implicit references or linguistic noise. As an alternative, this study investigates supervised text classification to model and detect suicidality in Dutch-language forum posts. Genetic algorithms were used to optimise models through feature selection and hyperparameter optimisation. A variety of features was found to be informative, including token and character ngram bags-of-words, presence of salient suicide-related terms and features based on LSA topic models and polarity lexicons. The results indicate that text classification is a viable and promising strategy for detecting suicide-related and alarming messages, with F-scores comparable to human annotators (93% for relevant messages, 70% for severe messages). Both types of messages can be detected with high precision and minimal noise, even on large high-skew corpora. This suggests that they would be fit for use in a real-world prevention setting.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volumes 439â440, May 2018, Pages 61-78
Journal: Information Sciences - Volumes 439â440, May 2018, Pages 61-78
نویسندگان
Bart Desmet, Véronique Hoste,