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Supawit Marerngsit. A two-stage text-to-emotion depressive disorder screening assistance from online community text . Master's Degree(Information Technology Management). Mahidol University. Mahidol University Library and Knowledge Center. : Mahidol University, 2020.
A two-stage text-to-emotion depressive disorder screening assistance from online community text
การช่วยคัดกรองโรคซึมเศร้าจากข้อความไปหาอารมณ์สองขั้วในข้อความในสังคมออนไลน์
Name: Supawit Marerngsit
MeSH:
Depression, Mental
Abstract:
Major Depressive Disorder (MDD), is one of the most serious mental diseases that can occur in anyone regardless of age or gender. Even though the symptoms of MDD are similar to regular emotional sadness, its impact is much worse and cloud lead to committing suicide. Nowadays, almost all people regularly use social media to communicate and express their opinions where the emotion could be impliedly illustrated through the textual conversation which leads to the implication to the possible sign of depression. This research presents a two-stage predictive model for MDD's risk screening assistance by using emotion weight based on textual data from social community. The messages are identified in six emotional dimensions; angry, bored, excited, scared, happy, and sad. These emotions are then categorized into 6 emotion-based clusters using DBSCAN algorithm and examined by medical and psychological experts with Patient Health Questionnaire-2. The labeled clusters are used to train and optimize classification models for each screening question with several algorithms; Decision Tree, Random Forest, and Gradient Boosted Tree. The experimental results show that the Gradient Boosted Tree is the best model for Q1 and the Random Forest is the best model for Q2 with 98.32% and 99.98%, accuracy respectively. This research will be beneficial in the further study in identifying depression from text-based emotion.
Mahidol University. Mahidol University Library and Knowledge Center
Address:
NAKHONPATHOM
Email:
liwww@mahidol.ac.th
Name: Sotarat Thammaboosadee
Role:
Thesis Advisors
Role:
Thesis Advisors
Name: Taweesak Samanchuen
Role:
Thesis Advisors
Created:
2020
Modified:
2024-04-24
Issued:
2024-04-24
วิทยานิพนธ์/Thesis
application/pdf
eng
DegreeName: Master of Science
Level: Master's Degree
Descipline: Information Technology Management
Grantor: Mahidol University
©copyrights Mahidol University
RightsAccess:
ใช้เวลา
-0.772234 วินาที
Supawit Marerngsit
| Title | Contributor | Type |
|---|---|---|
| A two-stage text-to-emotion depressive disorder screening assistance from online community text
มหาวิทยาลัยมหิดล Supawit Marerngsit | Sotarat Thammaboosadee Somkiat Wattanasirichaigoon Taweesak Samanchuen | วิทยานิพนธ์/Thesis |
Sotarat Thammaboosadee
Somkiat Wattanasirichaigoon
| Title | Creator | Type and Date Create |
|---|---|---|
| Descriptive and predictive data mining models for sepsis and septic shock patients treatments
มหาวิทยาลัยมหิดล Sotarat Thammaboosadee;Somkiat Wattanasirichaigoon;Supaporn Kiattisin | Sakulrat Khunsoongnoen | วิทยานิพนธ์/Thesis |
| A two-stage text-to-emotion depressive disorder screening assistance from online community text
มหาวิทยาลัยมหิดล Sotarat Thammaboosadee;Somkiat Wattanasirichaigoon;Taweesak Samanchuen | Supawit Marerngsit | วิทยานิพนธ์/Thesis |
| Human resource analytics adoption framework for high-performance state-owned enterprises (HPSOEs)
มหาวิทยาลัยมหิดล Sotarat Thammaboosadee;Somkiat Wattanasirichaigoon;Taweesak Samanchuen | Suchittra Pongpisutsopa | วิทยานิพนธ์/Thesis |
Taweesak Samanchuen