AI for social good
Suicide is a prevalent global issue that affects people of all ages and regions, with 703,000 people taking their own life every year. Suicide is a tragic event that not only impacts individuals but also has lasting effects on their loved ones. Globally, suicide is the fourth leading cause of d...
Saved in:
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2023
|
| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/166073 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 總結: | Suicide is a prevalent global issue that affects people of all ages and regions, with 703,000
people taking their own life every year. Suicide is a tragic event that not only impacts
individuals but also has lasting effects on their loved ones. Globally, suicide is the fourth
leading cause of death among 15–29-year-olds. With the recent development in machine
learning and prevalence of social media, it warrants a further exploration in this problem.
This project explores the use of machine learning to aid in suicide prevention efforts by
analyzing data from popular social media platforms, Twitter and Reddit. Various techniques
such as CNN, LSTM, GRU, and Transfer Learning were implemented to identify text with
suicidal ideation. Additionally, a Twitter bot was developed to detect the presence of suicidal
ideation and provide support to those in need. Limitations of the project, such as the difficulty
of identifying humor and sarcasm in text, are discussed, and potential future directions,
including multi-task learning and chatbot-based psychological assessments, are proposed.
Ultimately, this project highlights the importance of early intervention in preventing suicide
and demonstrates the potential of machine learning in suicide prevention efforts. |
|---|