互聯網愈趨成熟之發展與行動裝置之普及，且使用者對於社群媒體與即時通訊軟體的高黏著度，讓許多品牌與企業開始把產品服務，從既定介面操作轉變到人與人最基本的互動方式：「交談」上，繼而開啟聊天機器人之對話式介面的契機與商機。
如何建構符合使用情境之聊天機器人個性，繼而提高對話式互動體驗之使用意願，為一重要議題。本研究以「外放」--「內斂」人格維度之語言風格的相關文獻作為聊天機器人個性語句的參考，設計與建構個性不同的腳本式聊天機器人實驗原型，而機器人的使用情境為基礎理財知識查詢之「資訊查詢」情境。再根據文獻探討與統整，提出四項影響對話式互動體驗之相關構面：聊天機器人功能性、社會臨場感、信賴度與聊天機器人性別，作為本研究架構與評估聊天機器人個性和使用感知的相關依據。實驗以年輕族群為研究對象，採用觀察、問卷調查與訪談等研究方法收集資料。
透過文獻探討、量表調查與訪談、實驗分析，彙整歸納本研究之結論為：(1)受測者的確能透過不同個性之聊天機器人的對話語句，感知到其個性差異，因此當研究者需要建構聊天機器人個性特徵時，找到合適之人格模型的語言風格作為語句的參考，是非常有效率與適宜使用的工具；(2)影響對話式互動體驗之相關構面中，以信賴度影響感知與使用意願之程度最高。內斂機器人語句的語言風格，可讓使用者感知到較高的功能性與信賴度；外放機器人語句的語言風格，則讓使用者感知到較高的社會臨場感；(3)聊天機器人個性化確實會影響使用感知與使用意願，且以個性特徵之對話語句與功能性、社會臨場感、信賴度一同探討感知與意願時，可得出在理財知識查詢的使用情境下，內斂機器人的個性特徵，較適合作為此情境下可運用於機器人個性化的人格模型。
根據研究成果，本研究可作為在建構聊天機器人個性化時的設計參考架構，為聊天機器人之對話式互動體驗提供有用的建議。

Because of the advancement of Internet technology and wide diffusion of mobile devices, smartphone users are strongly bound to social media and instant messaging applications. Under such circumstances, various brands and businesses have transformed the way their products and services work from interface operation to chat—the most fundamental interaction between human beings. This change has fostered the development of conversational user interfaces with numerous business opportunities.
Furthermore, this change highlights the importance of developing favorable personalities for chatbots according to different scenarios to increase users’ willingness to engage in conversational interactions with computers. In this study, texts reflecting the language styles of an extraversion or introversion personality dimension were introduced as reference materials for chatbots. These scripted chatbots were designed to represent either of the two personality dimensions, with dialogues focusing on queries of basic wealth management information. Through literature review, four dimensions influencing conversational interactions were then proposed as references for the framework of the study and the assessment of personality dimensions and user perception: chatbot functionality, social presence, trust, and chatbot gender. The study investigated the young generation with research methods such as observation, questionnaire surveys, and interviews.
The results from literature review, scale questionnaires, and study analysis revealed three findings: (1) Participants were able to perceive personality difference through conversations with chatbots of different personality dimensions. Therefore, texts reflecting the language styles of certain personality dimensions can be a highly efficient and suitable tool for researchers who look to construct the personality traits of a chatbot; (2) Among the dimensions influencing conversational interactions, trust had the most significant impact on perception and willingness of usage. The linguistic output of an introvert chatbot led to higher user perception of functionality, while that of an extravert chatbot contributed to higher user perception of social presence; (3) Personalization of chatbot services does affect user perception and their willingness of usage. Personalized dialogues, functionality, social presence, and trust are relevant to user perception and willingness. The finding indicated the personality traits of an introvert chatbot are ideal for the prototype of a personalized chatbot providing query services of wealth management information.
This study serves as a reference for chatbot personality designs and provides useful suggestions for improving user experience of conversational interaction with chatbots.

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