對於影視作品創作來說，優秀的故事劇本是一部作品成功重要的因素之一。在過去製片與導演挑選劇本需要耗費大量的時間與人力，且難以統一標準與增加效率。因此本論文透過機器學習中BERT-base 和 MLP的組合演算法模型，對小說人物性格進行大五人格模型的分析，並採用「對立原則」詮釋角色在故事發展中性格的變化，以篩選出引人入勝的角色塑造，並透過成對樣本T檢定，檢測出在此方法下角色性格確實產生了顯著性的變化。最後再使用Tableau 雲端視覺化分析工具，將小說性格分析結果以互動式視覺化介面展現，提供一個能夠快速了解角色與故事發展，以達到輔助故事創作與篩選的工具。本論文同時透過深度訪談的方式，確認了這套研究工具確實替實務工作者帶來工作上的幫助，可作為未來相關研究及數位人文應用發展之參考。

An excellent story script is one of the essential factors for the success of the entertainment industry. However, producers and directors usually spend a lot of time and effort determining scripts from candidates. This paper employs a learning model with BERT-base and MLP to analyze the character in the novel with Big Five personality traits and use the principle of antagonism to interpret the personality of character changes in the story's development. The paired sample T-test shows the proposed method of this thesis can detect the character's personality and their differences in the novel. Then, an interactive visualized dashboard supported by Tableau was used at the end of this thesis to provide the readers to comprehend the development of characters rapidly and assist the producers and directors in determining a suitable story before reading the entire novel.

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