Identifying suicidal emotions on social media through transformer-based deep learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-022-04060-8.pdf
Reference75 articles.
1. Venek V, Scherer S, Morency L-P, Rizzo A, Pestian J (2017) Adolescent suicidal risk assessment in clinician-patient interaction. IEEE Trans Affect Com 8(2):204–215. https://doi.org/10.1109/TAFFC.2016.2518665
2. Caicedo R, Gómez J, Sasieta H (2020) Assessment of supervised classifiers for the task of detecting messages with suicidal ideation. Heliyon 6:04412. https://doi.org/10.1016/j.heliyon.2020.e04412
3. Platt S, Arensman E, Rezaeian M (2019) National suicide prevention strategies – progress and challenges. Crisis 40:75–82. https://doi.org/10.1027/0227-5910/a000587
4. Ji S, Yu C, Fung S-f, Pan S, Long G (2018) Supervised learning for suicidal ideation detection in online user content. Complexity 2018:1–10. https://doi.org/10.1155/2018/6157249
5. Sarsam S, Al-Samarraie H, Alzahrani A, Alnumay W, Smith A (2021) A lexicon-based approach to detecting suicide-related messages on twitter. Biomed Signal Process 65:102355. https://doi.org/10.1016/j.bspc.2020.102355
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. The Unveiling Distress: Harnessing NLP and Deep Learning to Identify Suicidal Signals in Tweets;International Journal of Technology, Innovation and Management (IJTIM);2024-06-06
2. Research on automatic error-checking in English short text translation by a neural network algorithm;Artificial Life and Robotics;2024-05-31
3. Emotion mining for early suicidal threat detection on both social media and suicide notes using context dynamic masking-based transformer with deep learning;Multimedia Tools and Applications;2024-05-25
4. Unraveling minds in the digital era: a review on mapping mental health disorders through machine learning techniques using online social media;Social Network Analysis and Mining;2024-04-04
5. Negative emotion detection on social media during the peak time of COVID-19 through deep learning with an auto-regressive transformer;Engineering Applications of Artificial Intelligence;2024-01
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3