Year: 2011
Type: conference-paper
Abstract: The present study is a trial in developing an automatic computerized coding framework with text mining techniques to identify the characteristics of redemption and contamination in life narratives written by undergraduate students. In the initial stage of text classification, the keyword-based classifier algorithm – product score model – performed more sensitive in finding the “change” elements in life stories comparing to the Decision Tree and Naïve Bayes models. The verbal features of life narratives were also discussed to enhance the classification accuracy further in assessing students’ personality adaption.
Institution: University of Twente
Language: English
Topic: Mental Health via Writing
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2400699692