Text Based Deception Detection Using a Hashing Algorithm and Machine Learning Techniques
DOI:
https://doi.org/10.58564/IJSER.3.1.2024.148Keywords:
Deception Detection; Lying Detection; Machine Learning; text classificationAbstract
One of the most challenging goals in the fields of law enforcement and the court rooms is the ability to detect deception and false information, this is due to the major role it has on national security and the justice system. One of the most important ways recent literatures has explored to overcome this challenge, is detecting deception using artificial intelligence techniques to find patterns in verbal and nonverbal features. Text based analysis has been one of the most important modals for this task since written text can be found in transcribed audio, emails, online messaging services, news articles, and many more. In this work, a combination of machine learning techniques and data processing using hashing algorithms is used applied to n-gram feature representation on two of the largest datasets in deception detection field. Together, results of up to %94.59 accuracy were achieved. The paper reviews the most common techniques used in recent literature, it also details the methodology followed for data processing and model training to achieve these results.
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