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A visual risk identification and early warning research for college net loan based on microblog texts

Author

Listed:
  • Ruijun Zhang

    (Wuhan University of Science and Technology
    Wuhan University of Science and Technology)

  • Caiyan Lin

    (Wuhan University of Science and Technology
    Wuhan University of Science and Technology, Huangjiahu Campus)

  • Zeping Tong

    (Wuhan University of Science and Technology)

Abstract

By analyzing microblog texts, a visual early warning research of college net loans is conducted in this paper to effectively reduce the negative impact of illegal Internet loans (abbreviated as "net loans") on college students' lives. Two calculation models are proposed in our research: One is the Identification Model of Risk Degree (IMRD) based on the security level of microblog texts about net loans. The other is the Calculation Model of Relationship Closeness (CMRC) based on three dimensions: user's relevant relationship, interaction strength, and interest similarity. IMRD is used to identify the risk of microblog net loan texts, and determine whether to early warn or not. CMRC is utilized to acquire a net loan communication map by describing the closeness level between net loan microblog publishers and their followers, and analyzing the possibility of retweeting. A visual monitoring and early warning platform is constructed based on these two models. With this platform, further spread of net loan information can be prevented by analyzing the graph and cutting off key nodes in time. The early warning mechanism of this research can effectively alleviate the negative influence of illegal net loans.

Suggested Citation

  • Ruijun Zhang & Caiyan Lin & Zeping Tong, 2021. "A visual risk identification and early warning research for college net loan based on microblog texts," Risk Management, Palgrave Macmillan, vol. 23(4), pages 261-281, December.
    • Handle: RePEc:pal:risman:v:23:y:2021:i:4:d:10.1057_s41283-021-00078-3
    DOI: 10.1057/s41283-021-00078-3
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    References listed on IDEAS

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    1. William Bosshardt & William B. Walstad, 2018. "Does studying economics in college influence loan decisions later in life?," The Journal of Economic Education, Taylor & Francis Journals, vol. 49(2), pages 130-141, April.
    2. Kristina Eriksson-Backa & Kim Holmberg & Stefan Ek, 2016. "Communicating diabetes and diets on Twitter - a semantic content analysis," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 16(1), pages 8-24.
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    Cited by:

    1. Ming-Fu Hsu & Chingho Chang & Jhih‐Hong Zeng, 2022. "Automated text mining process for corporate risk analysis and management," Risk Management, Palgrave Macmillan, vol. 24(4), pages 386-419, December.

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