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      Analysis of fictional characters in the context of artificial intelligence and big data: taking A Dream of Red Mansions for example

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      Digital Scholarship in the Humanities
      Oxford University Press (OUP)

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          Abstract

          This article uses artificial intelligence and big data to process the dialogs of the characters in A Dream of Red Mansions through Chinese psychoanalysis system, and obtains the prediction scores of the characters’ big-five personality. Then, the validity of this method is determined by examining the verification of the prediction scores by literature and fiction. Through the ecological identification and analysis of the personality characteristics in A Dream of Red Mansions, we find that Bao-Yu Jia in the novel has obvious openness, agreeableness, and extroversion; Dai-Yu Lin has very low extroversion, strong emotionality, and agreeableness; and Bao-Chai Xue has strong extroversion, agreeableness, and conscientiousness. The above prediction results are supported by relevant research literature and the novel itself. This shows that in the context of artificial intelligence and big data, the prediction of fictional characters’ personalities through literary intelligence analysis is helpful for us to understand the humanistic spirit or social idea behind literary works in a deeper and objective way. This research method is a beneficial supplement to the traditional literature and art research.

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          Most cited references43

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          An alternative "description of personality": the big-five factor structure.

          In the 45 years since Cattell used English trait terms to begin the formulation of his "description of personality," a number of investigators have proposed an alternative structure based on 5 orthogonal factors. The generality of this 5-factor model is here demonstrated across unusually comprehensive sets of trait terms. In the first of 3 studies, 1,431 trait adjectives grouped into 75 clusters were analyzed; virtually identical structures emerged in 10 replications, each based on a different factor-analytic procedure. A 2nd study of 479 common terms grouped into 133 synonym clusters revealed the same structure in 2 samples of self-ratings and in 2 samples of peer ratings. None of the factors beyond the 5th generalized across the samples. In the 3rd study, analyses of 100 clusters derived from 339 trait terms suggest their potential utility as Big-Five markers in future studies.
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            Stability and change of personality across the life course: the impact of age and major life events on mean-level and rank-order stability of the Big Five.

            Does personality change across the entire life course, and are those changes due to intrinsic maturation or major life experiences? This longitudinal study investigated changes in the mean levels and rank order of the Big Five personality traits in a heterogeneous sample of 14,718 Germans across all of adulthood. Latent change and latent moderated regression models provided 4 main findings: First, age had a complex curvilinear influence on mean levels of personality. Second, the rank-order stability of Emotional Stability, Extraversion, Openness, and Agreeableness all followed an inverted U-shaped function, reaching a peak between the ages of 40 and 60 and decreasing afterward, whereas Conscientiousness showed a continuously increasing rank-order stability across adulthood. Third, personality predicted the occurrence of several objective major life events (selection effects) and changed in reaction to experiencing these events (socialization effects), suggesting that personality can change due to factors other than intrinsic maturation. Fourth, when events were clustered according to their valence, as is commonly done, effects of the environment on changes in personality were either overlooked or overgeneralized. In sum, our analyses show that personality changes throughout the life span, but with more pronounced changes in young and old ages, and that this change is partly attributable to social demands and experiences. 2011 APA, all rights reserved
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              Trait-names: A psycho-lexical study.

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                Author and article information

                Journal
                Digital Scholarship in the Humanities
                Oxford University Press (OUP)
                2055-7671
                2055-768X
                April 01 2022
                March 23 2022
                August 11 2021
                April 01 2022
                March 23 2022
                August 11 2021
                : 37
                : 1
                : 289-297
                Affiliations
                [1 ]College of Chinese Language and Literature, Xinyang College, Xinyang, China
                Article
                10.1093/llc/fqab064
                43cf02e9-50e1-4f0f-b1e6-dde9c792e051
                © 2021

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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