P2P online lending is a prominent manifestation of mobile financial innovation in the era of digital economy, which has aroused widespread concern and discussion among investors on the social networking platform. By studying the comments about P2P online lending on social networking platforms, we can identify the main concerns and topics of investors on the lending platforms. This has important reference value for the development and supervision of P2P online investors and platforms. This paper collects the investors’ comments on the Internet financial section of Shuimu Community as text data, by using Python and ROST CM6, through text data visualization and highfrequency feature word analysis, to study the implied economic information of the text data. It is found that the comments mainly focus on the platforms which have strong financial strength and risk control ability, and that the main concerns about P2P online lending platforms include the risk, profitability, user experience and novice help. The empirical results are of great significance to strengthen the self-construction and supervision of the P2P online platforms and the decisionmaking of the investors.