Textual sentiment of comments and collapse of P2P platforms : Evidence from China's P2P market

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Original languageEnglish
Article number101448
Journal / PublicationResearch in International Business and Finance
Online published2 Jun 2021
Publication statusPublished - Dec 2021


Textual sentiment affects the investment activities of investors in traditional financial markets. Peer-to-Peer (P2P) lending market, as one of the emerging and active Internet financial markets, has recently received considerable attention from academia. However, few related studies are available. This work examines the relationship between the textual sentiment derived from investors’ comments on P2P platforms and probability of platform collapse. We collect comments from an authoritative Chinese third-party P2P lending consulting platform and use a weakly supervised convolutional neural network to calculate the textual sentiment of each comment. Empirical results show that the extracted textual sentiment has a significant influence on a P2P platform's collapse. Furthermore, the “agreement” and “disagreement” from other investors of each comment are pivotal in predicting a P2P platform's failure. We find that the textual sentiment of comments regarding P2P platforms from investor communities provide insights into predicting platforms’ collapse in the near future.

Research Area(s)

  • Convolutional neural network, Investor comment, P2P platform collapse, Textual sentiment