其他摘要 | It is of great significance to study the psychology of ancient Chinese. The psychology of contemporary Chinese comes from the psychology of the ancients. Studying the psychology of the ancients can better promote the research of contemporary Chinese and reveal the deep connotation of Chinese psychology. The ancient Chinese thought has been tested by both practice and history. The ancient psychological thought is worth learning and using for reference. The study of ancient Chinese psychological thought can not only make up for the deficiency of western psychological thought but also provide a strong foundation for Chinese Psychological Science.Previous scholars have conducted a lot of research on the psychological analysis of the ancients, but there are few pieces of research on the psychological semantics based on the self-expression texts of the Chinese ancients, most of which are limited to quantitative research or qualitative analysis based on other's comments. Besides, the research materials used in the traditional methods are small in scale, and most of them use the research methods of expert evaluation and manual reading of literature, so it is difficult to be used in the study of the group of ancient people in large time. Based on big data and artificial intelligence technology, this paper realizes the automatic analysis of ancient people's psychology based on a large-scale corpus, which breaks through the limitations of traditional methods, and is more suitable for large-scale group research; in this research method, we take the ancient people's self-expression text as the research material and carry on the psychological semantic analysis, which is more objective than other methods. We also introduced the Big Five personality model of modern psychology into the personality analysis of the ancients, which can better explain the psychology of the ancients with modern psychological theory.The basis of using big data to analyze ancient Chinese text is word segmentation. Firstly, this paper proposes a word segmentation method based on the dictionary CCIDict. With the development of the Internet, more and more online ancient Chinese datasets provide a new opportunity for the study of ancient Chinese corpus. We use the big data processing method to collect, process, and transform the data, and get a basic dictionary containing 331516 words; then we propose a New Word Discovery method based on multi-feature fusion, which integrates n-gram word frequency, mutual information, information entropy, and location probability to extract new words from the large-scale corpus and form a candidate dictionary; finally, we form a fusion basic dictionary and a candidate dictionary. The combined Dictionary of the dictionary includes all CC-LIWC words. By comparison, it is found that the forward maximum matching algorithm using combination dictionary CCIDict has the highest accuracy. Compared with the open-source Jia Yan tokenizer, the F value of our tokenizer is increased by 14 % , and better results are achieved. It also lays a foundation for the analysis of the psychological semantics of ancient Chinese texts by using big data.Personality analysis is an important part of the psychological research of the ancients. Due to the limitation of resources, the traditional research methods of psychological biography have certain limitations for the large-scale longitudinal study of ancient Chinese historical figures. With the development of artificial intelligence technology, transfer learning provides a new idea for the psychological research of the ancients. Microblog tweets are modern people's self-expression on the Internet, which can reflect the personality tendency of individuals. In the corresponding ancient books, autobiography, letters, and imperial edicts are also a kind of self-expression. Through the analysis of self-expression text, we can understand the personality feature of historical figures with different roles in ancient times. We use the microblog data of modern people as the source domain and the Autobiography of ancient people as the target domain to predict the big five personalities of ancient historical figures through the training transfer learning model. We propose UERDA and SERDA models. UERDA adds information entropy in the process of distribution adaptation to realize unsupervised domain adaptation based on regression tasks. SERDA adds a small number of labeled samples based on UERDA to improve the accuracy of the model in the regression task. Compared with the traditional algorithm PCA, the performance index RMSE of UERDA is increased by 2.23 on average; SERDA is similar to the traditional algorithm PCA The average performance index RMSE is increased by 3.16. The results show that transfer learning has achieved good performance in the prediction of the Big Five personality of ancient Chinese people, which opens up a new way for the study of social change in a large period through the quantitative way.To prove the validity of the method of historical and psychological analysis of ancient emperors. In a sense, the imperial edict is the emperor's self-expression text, which can reflect the emperor's psychological features. We combine our tokenizer with CC-LIWC to analyze the psychological semantic characteristics of the imperial edict and then explain the psychological laws in social changes. The results show that power has a significant impact on the duration of the Dynasty and the population. Power can explain the duration of 38.3 % , but there is no significant correlation between power and land area. Among the famous historical figures, Zhuge Liang was the Prime Minister of the Shu Han Dynasty, who presided over the Court Affairs for Liu Bei and was a well-known ancient figure. We chose Zhuge Liang as the object of analysis and analyzed Zhuge Liang's Big Five personality characteristics. The results show that the result of the SERDA is similar to that of artificial evaluation, and also in line with people's subjective feelings.From the perspective of big data and artificial intelligence, this paper puts forward a series of methods to study ancient people's psychology and realizes the psychological analysis of the individual or group of ancient Chinese people. The data results show that the research methods of this paper can be better applied to the psychological research of the ancient people, especially in the research of social change in a large period. |
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