一个心理语言NLP框架用于欺骗和情绪的法医文本分析
Jonathan Adkins1,2, Ali Al Bataineh2,3, Anthos Khanal2,3
1Senator Patrick Leahy School of Cybersecurity and Advanced Computing, Norwich University, Northfield, VT, United States.
Frontiers in artificial intelligence
|November 6, 2025
概括
这项研究使用自然语言处理 (NLP) 和心理语言分析来识别虚构案件中的嫌疑人. 该方法有效地检测欺骗和情绪,改善从大型候选人池中识别嫌疑人的能力.
科学领域:
- 心理语言学 心理语言学
- 计算语言学 计算语言学
- 法医心理学 法医心理学
背景情况:
- 心理语言学探讨了人类心理与语言之间的联系.
- 之前的研究利用自然语言处理 (NLP) 来从有限的数据集中识别嫌疑人.
- 大型语言模型 (LLM) 为生成复杂情景进行分析提供了新的途径.
研究的目的:
- 开发一种微妙的方法来逆向工程嫌疑人的心理语言特征.
- 加强从更大,更多样化的候选人群中识别感兴趣的人.
- 测量与欺骗,情感和主观性相关的语言线索.
主要方法:
- 应用n-grams,隐性迪里克莱特分配 (LDA) 和词向量.
- 对欺骗,情感和主观模式的分析.
- 专注于对嫌疑人进行分析的实体与主题的相关性.
主要成果:
- 在一个虚构的谋杀案中成功确定了有罪的当事人.
- 在更大,更多样化的语料库中证明了方法的有效性.
- 量化心理语言线索,以改善嫌疑人的识别.
结论:
- 开发的NLP和心理语言学方法为识别感兴趣的个体提供了一个强大的方法.
- 该研究强调了分析法医应用语言特征的潜力.
- 这项研究扩展了之前的工作,采用了更大的范围和多样化的数据集.
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