This study uses a two-stream multivariate data embedding network and FLAT model to effectively integrate text structure and linguistic information to enhance the performance of named entity recognition. In addition, named entity recognition and literary narrative analysis were carried out using linear chain conditional random field and Apriori algorithm, and literary character narratives and knowledge graphs were constructed. Finally, the characteristics and differences between Chinese and Western literature are deeply explored through econometric analysis and character similarity analysis, and it is found that the differences in geographic environment and socio-economic characteristics profoundly impact Chinese and Western literary art and poetics. The most fundamental difference between Chinese and Western societies lies in the commercial character of Western socio-economics, while China is more rural. The study reveals the uniqueness and intersection of the two civilizations in literary creation, providing a new perspective and theoretical support for cross-cultural academic dialogue.