GENERATIONAL DIFFERENCES IN THE IMAGE OF TEXT-BASED ONLINE COUNSELING: TEXT ANALYSIS WITH DEEP LEARNING TECHNOLOGY

Abstract

Text-based online counseling services are rapidly spreading, especially among younger generations. However, previous research on text-based online counseling is limited to young users in Western countries. Given its potential utility for broader populations, description of the public image of the service is necessary to reach broader populations. The current study aimed to describe public images of text-based online counseling in Japan, focusing on generational differences. An online survey asked Japanese participants (N = 614) from a wide age range (M = 41.77; SD = 11.98, range = 20 to 76) to freely describe their image and impressions of “SNS counseling,” the Japanese term for text-based counseling. We quantified each description with the Bidirectional Encoder Representations from Transformers (BERT) algorithm, a deep learning technology for natural language processing. We explored the components of images of text-based online counseling that linearly correlate with age. The main result indicated that the image of text-based online counseling among younger participants clustered around lightness, with both positive and negative connotations. Younger participants regarded text-based online counseling as easy to access but less serious. The image of text-based online counseling among older participants indicated that they were anxious about not being able to see the “face” of the counselor, and were concerned about security and privacy.