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Fraud and Deception Detection: Text-Based Data Analytics

In: Alternative Data and Artificial Intelligence Techniques

Author

Listed:
  • Qingquan Tony Zhang

    (University of Illinois Urbana-Champaign)

  • Beibei Li

    (Carnegie Mellon University)

  • Danxia Xie

    (Tsinghua University)

Abstract

With the trend of increasingly complex big data, how to handle and improve the authenticity of data has become an important issue related to the credibility of data. This chapter discusses how to imitate and detect similar applications and how to identify fake reviews by machine learning and various statistical methods using deceptive applications and fake reviews as examples.

Suggested Citation

  • Qingquan Tony Zhang & Beibei Li & Danxia Xie, 2022. "Fraud and Deception Detection: Text-Based Data Analytics," Palgrave Studies in Risk and Insurance, in: Alternative Data and Artificial Intelligence Techniques, chapter 0, pages 185-198, Palgrave Macmillan.
    • Handle: RePEc:pal:psircp:978-3-031-11612-4_10
    DOI: 10.1007/978-3-031-11612-4_10
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