Research on Characterization and Shaping of Chinese Heroic Characters in Online Media Based on Deep Neural Network Evaluation

Abstract

Shaping the image of heroic characters is an important task of melodramatic films and TV dramas, whether they are revolutionary heroes, combat heroes, leader heroes, or civilian heroes, which have always been the key objects of melodramatic films and TV dramas. However, the traditional melodramatic films and TV dramas are facing many bottlenecks in the acceptance of heroic characters in the new era. In this paper, in order to obtain a richer character text, we divide the denotation elimination into two parts; one is the denotation elimination without considering the zero pronoun phenomenon, which is mainly done by the existing end-to-end neural codenotation algorithm, and the other is the attention-based algorithm model for the zero pronoun phenomenon. Analyzing this result from the perspective of the algorithmic model, it can be speculated that the lexical vector has a superior performance in the overall predicted character score, indicating that in the Big Five personality analysis for characters, the character’s personality is more reflected in lexicality, and the scores on a person’s Big Five personality dimensions can be indirectly reflected by the frequency of using different lexicalities. The similarities and differences among heroes are explored to create a popular hero image.