In order to investigate the influences of borrower information on the decision-making, we collected data for 35,485 individual loan requests from Moneyauction, the largest P2P lending platform in South Korea, and analyzed the determinants of borrower and lender decision-making, adopting a logistic regression model. Specifically, we included various linguistic variables, generated by Korean Linguistic Inquiry and Word Count software, in order to analyze the effect of language use. Our research findings show that while a borrower’s demographic traits and linguistic style do have influential effects on participants’ decision-making, their relative importance is much lower than that of financial and loan request profiles.
All Science Journal Classification (ASJC) codes
- Economics and Econometrics