The purpose of this study is to explore the changing factors of platform business regulation policy. By applying the flash point concept presented by Thelen (2018), attention was paid to which issues formed a public consensus and even drew public opinion on the formation of regulations for platform businesses. Text mining techniques such as word frequency analysis, weighted log Odds ratio analysis, and topic modeling analysis were conducted. The structural power arising from the consumer - platform business alliance delayed regulation for a certain period of time, but the rapid spread of specific flash points was linked to changes in regulatory policy for platform business. This study is meaningful in that it theoretically developed the process of regulating and responding to platform business in a Korean context.

platform business regulation , policy change , text mining , topic modeling , Coupang