Complementing Borich Needs Assessment with Text Mining by Natural Language Processing

• In Event: GSIC Poster Session I

Abstract

This study explored a possibility of complementing results of Borich needs assessment model by implementing results of text mining by Natural Language Processing followed with principal component analysis, and co-occurrence analysis. The results show that NLP can provide complementary explanations that lead to better understandings of Borich needs assessment model.

Authors

• Yewon Kim, Ewha womans university

• Ja-yoon Lee, Seoul National University

• Jaehee Noh, Seoul National University

• John Park, United Nations University