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

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  • Wang, Chao
  • Zhang, Yue
  • Zhang, Weiguo
  • Gong, Xue

Abstract

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.

Suggested Citation

  • Wang, Chao & Zhang, Yue & Zhang, Weiguo & Gong, Xue, 2021. "Textual sentiment of comments and collapse of P2P platforms: Evidence from China's P2P market," Research in International Business and Finance, Elsevier, vol. 58(C).
    • Handle: RePEc:eee:riibaf:v:58:y:2021:i:c:s0275531921000696
    DOI: 10.1016/j.ribaf.2021.101448
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    Cited by:

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    2. Nigmonov, Asror & Shams, Syed & Alam, Khorshed, 2022. "Macroeconomic determinants of loan defaults: Evidence from the U.S. peer-to-peer lending market," Research in International Business and Finance, Elsevier, vol. 59(C).
    3. Miwa, Kotaro, 2022. "The informational role of analysts’ textual statements," Research in International Business and Finance, Elsevier, vol. 59(C).

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    More about this item

    Keywords

    P2P platform collapse; Convolutional neural network; Investor comment; Textual sentiment;
    All these keywords.

    JEL classification:

    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • G29 - Financial Economics - - Financial Institutions and Services - - - Other
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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