Evolution of mental health information-seeking behavior: a longitudinal text mining analysis from the pre-pandemic to the COVID-19 endemic era

Abstract

Abstract This study investigates the longitudinal evolution of healthcare consumers’ information-seeking behavior regarding mental health issues, specifically depression, across the pre-pandemic (2018), peak-pandemic (2022), and post-pandemic endemic (2025) eras. Utilizing a large-scale dataset from South Korea’s major search portals, we employed advanced text mining techniques, including word frequency, TF-IDF, and Bigram analysis, to identify shifting consumer interests and evolving psychological needs. The results reveal that while “Depression” and “Treatment” remained primary concerns throughout the entire pandemic cycle, a notable strategic shift emerged in the 2025 endemic era. Consumers increasingly transitioned from general information searching toward actively seeking professional clinical interventions, as evidenced by a surge in keywords such as “Counseling” and “Hospital,” alongside a heightened focus on adolescent-specific mental health symptoms. Furthermore, concerns regarding postpartum depression persisted as a consistent priority across all analyzed periods. These findings underscore the enduring psychological impacts of COVID-19 and highlight a critical shift in consumer demand toward formal mental health infrastructure. By identifying emerging needs for vulnerable populations like adolescents and postpartum women, this research provides empirical evidence for developing targeted public health policies and specialized community-based services in the post-pandemic landscape.