ABSTRACT
Rumors about the COVID-19 vaccines are spreading rapidly on social media platforms, questioning their intentions and efficiency. Currently, chatbots are used to combat the risk of misinformation amplification during the pandemic. They provide users with information from trusted and reliable sources. However, most of the current COVID-19 chatbots are non-personalized and do not focus on the vaccination process, rather they focus on answering general questions and performing symptom checking. In this paper, an empathetic chatbot named “Vaxera” was developed to provide users with accurate and up-to-date information about COVID-19 and its vaccines specifically. Vaxera provides users with information regarding COVID-19 frequently asked questions, advice and precautions, available vaccines, rumors and myths, and travel regulations. Additionally, it clears the circulating misconceptions about the vaccines and motivates the users on social media platforms to get vaccinated in a friendly manner. It tries to build a bond with the users through empathy and humor, so users will not feel forced. The results showed positive feedback from the participants who found the chatbot friendly and informative, as it corrected multiple rumors they believed. Moreover, a significant increase in the participants’ intentions to get vaccinated was observed after interacting with the chatbot. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Users have different expectations while interacting with chatbots. However, current chatbots do not consider the users' preferences and needs, creating unpleasant biases towards certain user groups. User characteristics play a vital role in predicting preferences and thus eliciting better responses as advocated by Character Computing. A framework was proposed in the literature to build character-based chatbots with adjustable traits. In this paper, we customize the framework modules to build two chatbots for different domains using the same set of chatbot characters. First, we present a character-based chatbot for academic support. It provides students with information regarding the content, dates, timings, locations, and deadlines of their courses. Second, we present a character-based chatbot for COVID-19. It provides users with answers to frequently asked questions, advice and precautions, cases per country, and symptoms checking. Users can select their preferable chatbot character to interact with, and receive personalized responses accordingly. Moreover, we investigated the prediction of a user's favorite chatbot character based on their personality traits to create adaptable chatbots in the future. Finally, we investigated the effect of a chatbot's character on its likability and trustworthiness. © 2021 ACM.
ABSTRACT
Chatbots are becoming an attractive tool for people who seek medical advice due to their constant availability. Multiple healthcare chatbots were developed for different purposes such as delivering advice, booking appointments, and accessing medical records. Additionally, it was found that personalized healthcare chatbots affected the user experience positively, due to the addition of human empathy. Therefore, we propose building a character-based chatbot named 'Chasey' for COVID-19, to combat the risk of misinformation amplification during the pandemic. Chasey provides users with various COVID-19 information such as tracking the cases per country, giving advice, answering frequently asked questions, and performing symptoms checking. According to the selected chatbot character, users will receive personalized responses to their inquiries from verified sources. Moreover, we investigate how our chatbot implementation overcomes some of the challenges and limitations of healthcare and COVID-19 chatbots. Finally, an experiment was conducted to evaluate the chatbot's usability, as well as, the likability and trustworthiness of the chatbot characters. Overall, the participants were satisfied with the chatbot features and character change option. Moreover, significant results were found between the likability of the chatbot characters. © 2021 IEEE.