Forecasting Identity Theft Victims: Analyzing Characteristics and Preventive Actions through Machine Learning Approaches

Xiaochen Hua Department of Criminal Justice, Fayetteville State University, Fayetteville, North Carolina, USACorrespondence[email protected]

https://orcid.org/0000-0002-3060-8530

Xudong Zhangb Department of Computer Science, Graduate Center of the City University of New York, New York City, USA

Nicholas P. Lovrichc School of Politics, Philosophy and Public Affairs, Washington State University, Pullman, Washington, USA

https://orcid.org/0000-0002-9173-547X

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Xiaochen Hu, Jae-Seung Lee & Nicholas P. Lovrich. (2023) Do Commonly Recommended Preventive Actions Deter Identity Theft Victimization? Findings from NCVS Identity Theft Surveys. Journal of Crime and Justice 46:2, pages 172-193.
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Xiaochen Hu, Xudong Zhang & Nicholas Lovrich. (2020) Public perceptions of police behavior during traffic stops: logistic regression and machine learning approaches compared. Journal of Computational Social Science 4:1, pages 355-380.
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Forecasting Identity Theft Victims: Analyzing Characteristics and Preventive Actions through Machine Learning Approaches

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