Affective Conversational Agents

Callejas, Zoraida; López-Cózar, Ramón; Ábalos, Nieves; Griol, David

doi:10.4018/978-1-60960-617-6.ch009

Cited by 18 publications

(5 citation statements)

References 76 publications

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“…Participant 7 said the chatbot was "amazing". Personality can be a crucial factor in determining whether the user wants to utilise the chatbot again [23]. The chatbottest questionnaire contains a questions around the voice and tone of the chatbot -"Can you identify a specific voice and tone in the chatbot that is consistent throughout the conversation?…”

Section: Discussionmentioning

confidence: 99%

Assessing the Usability of a Chatbot for Mental Health Care

Cameron

Cameron²,

Megaw³

et al. 2019

Internet Science

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The aim of this paper is to assess the usability of a chatbot for mental health care within a social enterprise. Chatbots are becoming more prevalent in our daily lives, as we can now use them to book flights, manage savings, and check the weather. Chatbots are increasingly being used in mental health care, with the emergence of "virtual therapists". In this study, the usability of a chatbot named iHelpr has been assessed. iHelpr has been developed to provide guided self-assessment, and tips for the following areas: stress, anxiety, depression, sleep, and self esteem. This study used a questionnaire developed by Chatbottest, and the System Usability Scale to assess the usability of iHelpr. The participants in this study enjoyed interacting with the chatbot, and found it easy to use. However, the study highlighted areas that need major improvements, such as Error Management and Intelligence. A list of recommendations has been developed to improve the usability of the iHelpr chatbot.

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Section: Discussionmentioning

confidence: 99%

Assessing the Usability of a Chatbot for Mental Health Care

Cameron

Cameron²,

Megaw³

et al. 2019

Internet Science

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“…53 Besides functionality and performance, social skills, including personality and emotion, are also relevant for interacting with conversation agents. 54 , 55 Dissatisfaction can be generated in the user if these expectations are not met. 56 As stated by Mori et al, there is an uncanny valley effect regarding human empathy towards robots and other AI entities.…”

Section: Discussionmentioning

confidence: 99%

Assessing medical students’ perceived stress levels by comparing a chatbot-based approach to the Perceived Stress Questionnaire (PSQ20) in a mixed-methods study

Moldt¹,

Festl-Wietek²,

Mamlouk³

et al. 2022

DIGITAL HEALTH

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Objective Digital transformation in higher education has presented medical students with new challenges, which has increased the difficulty of organising their own studies. The main objective of this study is to evaluate the effectiveness of a chatbot in assessing the stress levels of medical students in everyday conversations and to identify the main condition for accepting a chatbot as a conversational partner based on validated stress instruments, such as the Perceived Stress Questionnaire (PSQ20). Methods In this mixed-methods research design, medical-student stress level was assessed using a quantitative (digital- and paper-based versions of PSQ20) and qualitative (chatbot conversation) study design. PSQ20 items were also shortened to investigate whether medical students’ stress levels can be measured in everyday conversations. Therefore, items were integrated into the chat between medical students and a chatbot named Melinda. Results PSQ20 revealed increased stress levels in 43.4% of medical students who participated ( N = 136). The integrated PSQ20 items in the conversations with Melinda obtained similar subjective stress degree results in the statistical analysis of both PSQ20 versions. Qualitative analysis revealed that certain functional and technical requirements have a significant impact on the expected use and success of the chatbot. Conclusion The results suggest that chatbots are promising as personal digital assistants for medical students; they can detect students’ stress factors during the conversation. Increasing the chatbot's technical and social capabilities could have a positive impact on user acceptance.

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“…Chatbot personality is defined as the stable pattern that dictates the behaviour of a CA [13,70,62], playing a crucial role in its perception by users and its level of acceptability [58], even possibly determining whether users will wish to interact with the chatbot again. [13] Personality can be embedded into a CA by using different channels [33], e.g. what contents it provides and how it speaks, and expressed by different linguistic styles [48].…”

Section: Chatbot Gender and Personalitymentioning

confidence: 99%

“…Personality has been found to offer consistency to the interaction [13,46], helping users feel that they are talking to only one person throughout the conversation [62]. Personality also improves the chatbot user experience [62] by enhancing conversational agents' likability and humanness, [65] as a pure information exchange gives way to a more empathetic and self-referencing language style, which is generally preferred and perceived as more realistic, [65] in particular when displaying agreeableness.…”

Section: Chatbot Gender and Personalitymentioning

confidence: 99%

The Impact of Gender and Personality in Human-AI Teaming: The Case of Collaborative Question Answering

Milella,

Natali,

Scantamburlo

et al. 2023

Lecture Notes in Computer Science

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This paper discusses the results of an exploratory study aimed at investigating the impact of conversational agents (CAs) and specifically their agential characteristics on collaborative decision-making processes. The study involved 29 participants divided into 8 small teams engaged in a question-and-answer trivia-style game with the support of a text-based CA, characterized by two independent binary variables: personality (gentle and cooperative vs blunt and uncooperative) and gender (female vs male). A semi-structured group interview was conducted at the end of the experimental sessions to investigate the perceived utility and level of satisfaction with the CAs. Our results show that when users interact with a gentle and cooperative CA, their user satisfaction is higher. Furthermore, female CAs are perceived as more useful and satisfying to interact with than male CAs. We show that group performance improves through interaction with the CAs, confirming that a stereotype favoring the female with a gentle and cooperative personality combination exists in regard to perceived satisfaction, even though this does not lead to greater perceived utility. Our study extends the current debate about the possible correlation between CA characteristics and human acceptance and suggests future research to investigate the role of gender bias and related biases in human-AI teaming.

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Affective Conversational Agents

Cited by 18 publications

References 76 publications

Assessing the Usability of a Chatbot for Mental Health Care

Assessing the Usability of a Chatbot for Mental Health Care

Assessing medical students’ perceived stress levels by comparing a chatbot-based approach to the Perceived Stress Questionnaire (PSQ20) in a mixed-methods study

The Impact of Gender and Personality in Human-AI Teaming: The Case of Collaborative Question Answering

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