IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i8p3293-d347072.html
   My bibliography  Save this article

Lender Trust on the P2P Lending: Analysis Based on Sentiment Analysis of Comment Text

Author

Listed:
  • Beibei Niu

    (College of Economics and Management, China Agricultural University, Beijing 100083, China)

  • Jinzheng Ren

    (College of Economics and Management, China Agricultural University, Beijing 100083, China)

  • Ansa Zhao

    (Agricultural Development Bank of China, Beijing 100045, China)

  • Xiaotao Li

    (College of Economics and Management, China Agricultural University, Beijing 100083, China)

Abstract

Lender trust is important to ensure the sustainability of P2P lending. This paper uses web crawling to collect more than 240,000 unique pieces of comment text data. Based on the mapping relationship between emotion and trust, we use the lexicon-based method and deep learning to check the trust of a given lender in P2P lending. Further, we use the Latent Dirichlet Allocation (LDA) topic model to mine topics concerned with this research. The results show that lenders are positive about P2P lending, though this tendency fluctuates downward with time. The security, rate of return, and compliance of P2P lending are the issues of greatest concern to lenders. This study reveals the core subject areas that influence a lender’s emotions and trusts and provides a theoretical basis and empirical reference for relevant platforms to improve their operational level while enhancing competitiveness. This analytical approach offers insights for researchers to understand the hidden content behind the text data.

Suggested Citation

  • Beibei Niu & Jinzheng Ren & Ansa Zhao & Xiaotao Li, 2020. "Lender Trust on the P2P Lending: Analysis Based on Sentiment Analysis of Comment Text," Sustainability, MDPI, vol. 12(8), pages 1-14, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3293-:d:347072
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/8/3293/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/8/3293/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dongyu Chen & Xiaolin Li & Fujun Lai, 2017. "Gender discrimination in online peer-to-peer credit lending: evidence from a lending platform in China," Electronic Commerce Research, Springer, vol. 17(4), pages 553-583, December.
    2. Chuanman You, 2018. "Recent Development of FinTech Regulation in China: A Focus on the New Regulatory Regime for the P2P Lending (Loan-based Crowdfunding) Market," Capital Markets Law Journal, Oxford University Press, vol. 13(1), pages 85-115.
    3. Siming Li & Zhangxi Lin & Jiaxian Qiu & Roozmehr Safi & Zhongyi Xiao, 2015. "How friendship networks work in online P2P lending markets," Nankai Business Review International, Emerald Group Publishing Limited, vol. 6(1), pages 42-67, March.
    4. Luigi Guiso & Paola Sapienza & Luigi Zingales, 2009. "Cultural Biases in Economic Exchange?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(3), pages 1095-1131.
    5. Riza Emekter & Yanbin Tu & Benjamas Jirasakuldech & Min Lu, 2015. "Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 54-70, January.
    6. Mingfeng Lin & Nagpurnanand R. Prabhala & Siva Viswanathan, 2013. "Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending," Management Science, INFORMS, vol. 59(1), pages 17-35, August.
    7. Erick Kauffmann & Jesús Peral & David Gil & Antonio Ferrández & Ricardo Sellers & Higinio Mora, 2019. "Managing Marketing Decision-Making with Sentiment Analysis: An Evaluation of the Main Product Features Using Text Data Mining," Sustainability, MDPI, vol. 11(15), pages 1-19, August.
    8. Francisco Guijarro & Ismael Moya-Clemente & Jawad Saleemi, 2019. "Liquidity Risk and Investors’ Mood: Linking the Financial Market Liquidity to Sentiment Analysis through Twitter in the S&P500 Index," Sustainability, MDPI, vol. 11(24), pages 1-13, December.
    9. Manconi, Alberto & Braggion, Fabio & Zhu, Haikun, 2018. "Can Technology Undermine Macroprudential Regulation? Evidence from Peer-to-Peer Credit in China," CEPR Discussion Papers 12668, C.E.P.R. Discussion Papers.
    10. Juanjuan Chen & Yabin Zhang & Zhujia Yin, 2018. "Education Premium In The Online Peer-To-Peer Lending Marketplace: Evidence From The Big Data In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(01), pages 45-64, March.
    11. Oded Netzer & Ronen Feldman & Jacob Goldenberg & Moshe Fresko, 2012. "Mine Your Own Business: Market-Structure Surveillance Through Text Mining," Marketing Science, INFORMS, vol. 31(3), pages 521-543, May.
    12. Jefferson Duarte & Stephan Siegel & Lance Young, 2012. "Trust and Credit: The Role of Appearance in Peer-to-peer Lending," The Review of Financial Studies, Society for Financial Studies, vol. 25(8), pages 2455-2484.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Honglin Xiong & Chongjun Fan & Hongmin Chen & Yun Yang & Collins Opoku ANTWI & Xiaomao Fan, 2022. "A Novel Approach to Air Passenger Index Prediction: Based on Mutual Information Principle and Support Vector Regression Blended Model," SAGE Open, , vol. 12(1), pages 21582440211, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wu, Bao & Liu, Zijia & Gu, Qiuyang & Tsai, Fu-Sheng, 2023. "Underdog mentality, identity discrimination and access to peer-to-peer lending market: Exploring effects of digital authentication," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    2. Jianwen Li & Jinyan Hu, 2022. "Migrants and default: Evidence from China," International Review of Finance, International Review of Finance Ltd., vol. 22(3), pages 472-505, September.
    3. Li, Jianwen & Hu, Jinyan, 2019. "Does university reputation matter? Evidence from peer-to-peer lending," Finance Research Letters, Elsevier, vol. 31(C), pages 66-77.
    4. Qun Chen & Ji-Wen Li & Jian-Guo Liu & Jing-Ti Han & Yun Shi & Xun-Hua Guo, 2021. "Borrower Learning Effects: Do Prior Experiences Promote Continuous Successes in Peer-to-Peer Lending?," Information Systems Frontiers, Springer, vol. 23(4), pages 963-986, August.
    5. Qun Chen & Ji-Wen Li & Jian-Guo Liu & Jing-Ti Han & Yun Shi & Xun-Hua Guo, 0. "Borrower Learning Effects: Do Prior Experiences Promote Continuous Successes in Peer-to-Peer Lending?," Information Systems Frontiers, Springer, vol. 0, pages 1-24.
    6. Croux, Christophe & Jagtiani, Julapa & Korivi, Tarunsai & Vulanovic, Milos, 2020. "Important factors determining Fintech loan default: Evidence from a lendingclub consumer platform," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 270-296.
    7. Xueru Chen & Xiaoji Hu & Shenglin Ben, 2021. "How do reputation, structure design and FinTech ecosystem affect the net cash inflow of P2P lending platforms? Evidence from China," Electronic Commerce Research, Springer, vol. 21(4), pages 1055-1082, December.
    8. Dongyu Chen & Xiaolin Li & Fujun Lai, 2023. "Shill bidding in lenders’ eyes? A cross-country study on the influence of large bids in online P2P lending," Electronic Commerce Research, Springer, vol. 23(2), pages 1089-1114, June.
    9. Dorfleitner, Gregor & Rad, Jacqueline & Weber, Martina, 2017. "Pricing in the online invoice trading market: First empirical evidence," Economics Letters, Elsevier, vol. 161(C), pages 56-61.
    10. Wang, Qi & Xiong, Xiong & Zheng, Zunxin, 2021. "Platform Characteristics and Online Peer-to-Peer Lending: Evidence from China," Finance Research Letters, Elsevier, vol. 38(C).
    11. Wu, Yu & Zhang, Tong, 2021. "Can credit ratings predict defaults in peer-to-peer online lending? Evidence from a Chinese platform," Finance Research Letters, Elsevier, vol. 40(C).
    12. Jianrong Yao & Jiarui Chen & June Wei & Yuangao Chen & Shuiqing Yang, 2019. "The relationship between soft information in loan titles and online peer-to-peer lending: evidence from RenRenDai platform," Electronic Commerce Research, Springer, vol. 19(1), pages 111-129, March.
    13. Lu, Haitian & Wang, Bo & Wang, Haizhi & Zhao, Tianyu, 2020. "Does social capital matter for peer-to-peer-lending? Empirical evidence," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    14. Jin, Ming & Yin, Mingmei & Chen, Zhongfei, 2021. "Do investors prefer borrowers from high level of trust cities? Evidence from China’s P2P market," Research in International Business and Finance, Elsevier, vol. 58(C).
    15. Liu, Aiping & Urquía-Grande, Elena & López-Sánchez, Pilar & Rodríguez-López, Ángel, 2023. "Research into microfinance and ICTs: A bibliometric analysis," Evaluation and Program Planning, Elsevier, vol. 97(C).
    16. Li, Zhiyong & Li, Aimin & Bellotti, Anthony & Yao, Xiao, 2023. "The profitability of online loans: A competing risks analysis on default and prepayment," European Journal of Operational Research, Elsevier, vol. 306(2), pages 968-985.
    17. Na Sun & Liangrong Song & Yan Sun, 2021. "Fuze Effect: A Landmine in the Way of Sustainable Development of FinTech—The Lessons from the Peer-To-Peer Risk Outbreak," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    18. Li, Jianwen, 2023. "MSMEs meet FinTech: Chance or challenge?," Finance Research Letters, Elsevier, vol. 57(C).
    19. Liu, He & Qiao, Han & Wang, Shouyang & Li, Yuze, 2019. "Platform Competition in Peer-to-Peer Lending Considering Risk Control Ability," European Journal of Operational Research, Elsevier, vol. 274(1), pages 280-290.
    20. Benjamin Käfer, 2016. "Peer-to-Peer Lending – A (Financial Stability) Risk Perspective," MAGKS Papers on Economics 201622, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

    More about this item

    Keywords

    P2P lending; public trust; sentiment analysis;
    All these keywords.

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3293-:d:347072. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.