Applying automatic text-based detection of deceptive language to police reports: Extracting behavioral patterns from a multi-step classification model to understand how we lie to the police
作者：
Highlights：
• VeriPol is an effective text-based lie detection model for police reports.
• Our model includes feature selection by L1 penalization and heuristic rules.
• Computational experiments on a real dataset show a validation accuracy of 91.
• A pilot study shows a lower bound on the empirical precision of 83%, approx.
• The model analysis provides linguistic insights of how people lie to the police.
摘要
•VeriPol is an effective text-based lie detection model for police reports.•Our model includes feature selection by L1 penalization and heuristic rules.•Computational experiments on a real dataset show a validation accuracy of 91.•A pilot study shows a lower bound on the empirical precision of 83%, approx.•The model analysis provides linguistic insights of how people lie to the police.
论文关键词：Lie detection,Information extraction,Predictive policing,Model knowledge extraction,Natural language processing,Decision support systems
论文评审过程：Received 30 October 2017, Revised 5 March 2018, Accepted 7 March 2018, Available online 8 March 2018, Version of Record 19 March 2018.
论文官网地址：https://doi.org/10.1016/j.knosys.2018.03.010
