企業首要目的是為獲利，過去許多研究顯示人格與許多的購買行為都具有相關性，因此若能掌握客群的人格，便有助於企業進行有效的行銷手段進而獲取利益。企業在傳統的人格評測方式上，花費在時間與人力的成本十分高昂，因此如何有效地對目標客群進行自動化人格判斷便是相當值得研究的議題。近年蓬勃發展的各式社群網站已成為使用者公開發表言論並與他人進行互動的平台，也因此有許多的研究投入並證實在社群網站中的行為與人格之間的關聯性，但社群網站的發展非常快速也十分多元，所以若能有一自動化人格判斷方法可以套用在不同的社群網站上方能增進人格判斷的方便性與完善性。本研究以自動化的主題判斷，分類使用者在Facebook上的貼文與喜好的粉絲專頁貼文，發展一以Facebook貼文判斷人格特質之方法。研究方法發現在五大人格中敏感度高的人，經常關注談論兩性與感情議題的粉絲專頁；常發表文創相關內容貼文的人，有著較高的開放性。

Many studies have shown that personality is related to purchase behaviors. Therefore, if you can grasp the personality of the customer group, it will help the company to carry out effective marketing and gain benefits. In the past, personality judging method wastes time and manpower. Therefore, how to effectively judge the target customers is a worthy issue. The social network flourished in recent years have become a platform for users to share and social. Actually, researchers have confirmed the relationship between social network behaviors and personality. The growing of social network is very fast, so an automated personality judgment method that can be applied to different social network is important. The study uses automated topics judgments to classify users' posts on Facebook and posts in fan page to develop a method for judging personality traits with Facebook posts. The research found people with high sensitivity pay attention to fan pages about gender and emotional issues; who publish cultural and creative posts have a high degree of openness.
Key words: Latent Dirichlet allocation(LDA); Machine learning; Personality prediction; Social network website.

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