The Korean Wave phenomenon is spreading around the world, and Indonesia is no exception. Based on Twitter data, Indonesia is the number one country that has the most K-Pop fans who express themselves through Twitter and can have both positive and negative impacts on the mental health of K-Pop fans. One of the mental health issues that concern researchers is the tendency of depression which is often associated with emotional reactivity. In this study, we will measure the emotional reactivity of K-Pop fans using an Artificial Intelligence (AI) model. Emotional reactivity is a form of negative emotionalexpression that can indicate an individual's mental health condition, such as depression. This study aims to recognize emotional reactivity by using an AI model to detect depressive tendencies. The participants in this study will be 500 late adolescents to early adults (age range 15-40 years) K-Pop fans and active Twitter users in Indonesia. This research will use data mining to analyse Twitter data and will use AI model to classify the emotion reactivity of twitter user. Quantitative methods with predictive correlation design willalso be used in this study. Regression will be used in analyzing the data. The researcher predicts that AI can detect emotional reactivity. We also predict that there is a role ofemotional reactivity detected by AI on depression tendency.

Emotional reactivity, artificial intelligence, depression, well-being, K-Pop

• Ade Putera Kemala, S.Kom., M.Kom.

• Dr. Esther Widhi Andangsari, M.Si., Psi.

• Greta Vidya Paramita, M.Psi., Psikolog

• Moondore Madalina Ali, B.Sc., M.Sc., Ph.D.