Classical Chinese literary texts are the core carrier of Chinese excellent traditional culture, bearing profound philosophical connotations and cultural values. However, due to the archaic language style, complex semantic system, and significant cultural differences between East and West, the accurate semantic parsing and effective cross-cultural dissemination of these texts face severe challenges. In response to the limitations of traditional semantic analysis methods (such as insufficient contextual understanding and over-reliance on manual annotation) and the lack of a systematic evaluation system for cross-cultural dissemination effects, this study proposes a deep learning-based integrated framework for semantic analysis and dissemination effect evaluation of classical Chinese literary texts. First, a Multidimensional Semantic Fusion Model (MSFM) based on improved BERT is constructed, which integrates lexical, syntactic, and cultural knowledge features to realize accurate parsing of implicit and explicit semantics in classical texts. Second, combining cultural dimension theory and communication effectiveness evaluation, a Cross-Cultural Dissemination Effect Evaluation Index System (CCDEIS) is established, which quantifies the dissemination effect from three dimensions: information fidelity, emotional resonance, and cultural identity. Third, experimental verification is carried out using a self-built corpus of classical Chinese literary texts (including The Analects, Tao Te Ching, and Book of Songs) and cross-cultural dissemination data from multiple regions. The results show that the MSFM model achieves an F1-score of 92.7% in semantic similarity and 89.3% in cultural connotation extraction, which is 8.5% and 10.2% higher than the traditional BERT and LSTM models, respectively. The CCDEIS index system can effectively evaluate the dissemination effect of different texts in different cultural contexts, with an evaluation consistency of 0.87. This study not only provides a new technical path for the digital protection and semantic mining of classical Chinese literary texts but also offers a scientific evaluation method for promoting the cross-cultural communication of Chinese traditional culture, which has important theoretical value and practical significance for cultural inheritance and global cultural exchanges.
Jianwei Yang (Mon,) studied this question.