Textual Descriptions and Situational Contexts: Evidence from P2P Lending

This study empirically analyzes borrower text descriptions in a peer-to-peer lending market using partial least squares structural equation models. It shows that people’s linguistic traits reflect their situational contexts in online communication media. Factors representing proxies of situational contexts have direct or indirect effects on borrower linguistic traits. Borrowers with lower credit scores, larger loans, and higher loan interest rates show stronger linguistic traits. These findings highlight the limitations of existing studies that focus solely on the relationship between language and personality, which is an invariant characteristic. The study also finds that an individual’s linguistic traits can influence a counterparty’s decision-making in a direction favorable to the individual by mitigating the negative effects of situational contexts on decision-making, and that people’s linguistic traits can signify their motivation and predict better behavioral outcomes. Through interdisciplinary linguistics and finance research, this study presents empirical evidence to support the systemic functional linguistics theory.