Automatic Psychological Text Analysis using Recurrent Neural Networks

Automatic Psychological Text Analysis using Recurrent Neural Networks

Zhang, Mirijam (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Interactive Intelligence)

Brinkman, W.P. (mentor)
Bruijnes, M. (graduation committee)
Hung, H.S. (graduation committee)

Delft University of Technology

Computer Science and Engineering

CSE3000 Research Project

2021-07-01

Schema therapy is a type of psychological treatment for people suffering from personality disorders. A schema is a core psychological state of mind that influences external behaviour through the development of coping styles. Current schema therapy is time inefficient and human-processed. Enabling automatic schema classification helps the overall goal of creating a chatbot that can classify schema modes from conversations. The goal of this research was to optimize a Recurrent Neural Network (RNN) model to classify patient’s schema modes from a dataset containing a recent emotional story from participants and are labeled with SMI questionnaire answers. Three RNN models were created: a binary classification Multilabel RNN, a binary classification Per-Schema RNN and a ordinal classification Per-Schema RNN. The results have shown that the binary classification Multilabel model scores an average F1-score of 0.48. The binary classification Per-Schema model scores an average F1-score of 0.49. While ordinal classification Per-Schema model performs with an average Spearman Coefficient of 0.15.

psychological text analysis
Recurrent Neural Network
cognitive behaviour therapy
therapy chatbot

http://resolver.tudelft.nl/uuid:045b3a57-6083-47ce-8417-599d312a637b

https://github.com/Mirijam1/Automatic_Psychological_Text_Analysis_RNN GitHub containing code

Student theses

bachelor thesis

© 2021 Mirijam Zhang