This study investigates how online search activities for shopping products in South Korea changed over time during the COVID-19 pandemic. Using weekly data from NAVER DataLab Shopping Insight (NDLSI) from 2017-2021, the study used singular value decomposition (SVD) analysis to identify major trends in online search activity. Before the pandemic, the main trend was a steady increase in searches, with a secondary seasonal pattern linked to temperature. After removing these trends, the analysis revealed a strong correlation between online search activity and the various waves of COVID-19 infections. Life/health, digital/home appliance, food, and childbirth/childcare products showed the strongest association with pandemic waves. The study emphasizes the importance of understanding how social behavior changes during pandemics to better prepare for future events.

Jiam Song, Kwangmin Jung, Jonghun Kam