【摘要】 【目的】提出一种基于叙事型文本重构的多维人格计算与分析方案，探索并验证数字技术在提升文学作品人物分析深度和广度上的潜力。【方法】研究过程包括文本重构、人格量化、模型构建和人格分析。首先，通过机器翻译、指代消解等技术抽取文本信息；其次，利用大语言模型获取人物人格描述，构建人格数据集；接着，采用深度学习框架LBA构建人格检测模型；最后，完成多维人格的数值计算与分析。【结果】所提自动化抽取方案在文本重构中，主体人物抽取效果显示准确率均超过89%,F1值均超过74%，文本内容拆解效果显示Rouge-L在各类文本的均值达到73.01%。构建的人格检测模型MPNDM的MSE指标比两个对比模型分别降低29.08%、8.72%。通过对《三国演义》全人物及代表性人物的人格分析，揭示了人物群体与个体在人格上的差异与变化。【局限】由于关于人物人格测度的理论与模型较为多样化，引入不同的理论模型可能得到不同的效果，因此模型泛化能力有待进一步检验与提升。【结论】本研究基于叙事文本重构，提出多维人格数值计算方案，并验证了其在人格量化、检测与分析方面的有效性，为人物形象鉴赏研究提供了数字人文的新路径。更多还原

【Abstract】 [Objective] This study presents a multidimensional personality computing framework based on narrative text reconstruction, aiming to explore the potential of digital technology in enhancing the depth and breadth of literary character analysis. [Methods] Our research process includes text reconstruction, personality quantification, model construction, and personality analysis. First, we extracted text information using technologies such as machine translation and coreference resolution. Second, we utilized a large language model(LLM) to generate personality descriptions of characters to construct a personality dataset. Third, we built a personality detection model using a deep learning framework. Finally, we conducted multidimensional personality computation and analysis. [Results] Experiments show that the proposed method achieves over 89% accuracy and 74% F1 in main character extraction, with an average Rouge-L of 73.01% for text segmentation. The personality detection model(MPNDM) outperforms baselines by reducing MSE by 29.08% and 8.72%, respectively. A case study on Romance of the Three Kingdoms demonstrates the model’s ability to capture both group and individual personality differences. [Limitations] Since theoretical models and measures of personality vary widely, introducing different theoretical models may yield different results; thus, the model’s generalization ability requires further verification and improvement. [Conclusions] The proposed framework offers a new digital humanities approach to character image appreciation in literary research.更多还原