Humour, Relationship Maintenance and Personality Matching in automated dialogue: A controlled study

Boni, Marco De; Richardson, Alannah; Hurling, Robert

doi:10.1016/j.intcom.2007.11.002

Cited by 14 publications

(9 citation statements)

References 29 publications

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“…No significant effect [23] 2 (5) Conversation memory (vs none) -No significant effect [36] No significant effect [36] No significant effect [36] Mixed positive [36] No significant effect [36] No significant effect [36] Mixed positive [ [50,67] No significant effect [67] Negative [67] No significant effect [65,67] 3 (7) Culturally tailored appearance (vs not) --No significant effect [68] -No significant effect [68] No significant effect [68] No significant effect [68] No significant effect c Multiple studies were reported in the article with similar results. d Similar results were additionally reported at a different time point in the study [39].…”

Section: Mixed Positive [36] •mentioning

confidence: 99%

“…Mixed positive [64] Positive [64] • No significant ef- [32] No significant effect [33] No significant effect [33] 3 ( [36] No significant effect [36,60] No significant effect [36] No significant effect [36] •…”

Section: Overviewmentioning

confidence: 99%

“…No significant effect [36] 3 ( 7) Personality (various) f -No significant effect [23,36] No significant effect [23,36] No significant effect [36] No significant effect [23,36] No significant effect [36] Mixed positive [36] •…”

Section: Overviewmentioning

confidence: 99%

“…Approximately 7% (3/41) of studies examined self-disclosure-whether the virtual assistant tells the user information about themselves-and found mostly positive effects [29,44,47]. Approximately 7% (3/41) of studies examined personality [36,60,61]. Although some positive and mixed positive effects were found [60,61], most effects were nonsignificant [36,60].…”

Section: Conversational Style and Relational Behaviormentioning

confidence: 99%

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Improving User Experience of Virtual Health Assistants: Scoping Review

Curtis¹,

Bartel²,

Ferguson³

et al. 2021

J Med Internet Res

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Background Virtual assistants can be used to deliver innovative health programs that provide appealing, personalized, and convenient health advice and support at scale and low cost. Design characteristics that influence the look and feel of the virtual assistant, such as visual appearance or language features, may significantly influence users’ experience and engagement with the assistant. Objective This scoping review aims to provide an overview of the experimental research examining how design characteristics of virtual health assistants affect user experience, summarize research findings of experimental research examining how design characteristics of virtual health assistants affect user experience, and provide recommendations for the design of virtual health assistants if sufficient evidence exists. Methods We searched 5 electronic databases (Web of Science, MEDLINE, Embase, PsycINFO, and ACM Digital Library) to identify the studies that used an experimental design to compare the effects of design characteristics between 2 or more versions of an interactive virtual health assistant on user experience among adults. Data were synthesized descriptively. Health domains, design characteristics, and outcomes were categorized, and descriptive statistics were used to summarize the body of research. Results for each study were categorized as positive, negative, or no effect, and a matrix of the design characteristics and outcome categories was constructed to summarize the findings. Results The database searches identified 6879 articles after the removal of duplicates. We included 48 articles representing 45 unique studies in the review. The most common health domains were mental health and physical activity. Studies most commonly examined design characteristics in the categories of visual design or conversational style and relational behavior and assessed outcomes in the categories of personality, satisfaction, relationship, or use intention. Over half of the design characteristics were examined by only 1 study. Results suggest that empathy and relational behavior and self-disclosure are related to more positive user experience. Results also suggest that if a human-like avatar is used, realistic rendering and medical attire may potentially be related to more positive user experience; however, more research is needed to confirm this. Conclusions There is a growing body of scientific evidence examining the impact of virtual health assistants’ design characteristics on user experience. Taken together, data suggest that the look and feel of a virtual health assistant does affect user experience. Virtual health assistants that show empathy, display nonverbal relational behaviors, and disclose personal information about themselves achieve better user experience. At present, the evidence base is broad, and the studies are typically small in scale and highly heterogeneous. Further research, particularly using longitudinal research designs with repeated user interactions, is needed to inform the optimal design of virtual health assistants.

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Section: Mixed Positive [36] •mentioning

confidence: 99%

Section: Overviewmentioning

confidence: 99%

Section: Overviewmentioning

confidence: 99%

Section: Conversational Style and Relational Behaviormentioning

confidence: 99%

See 2 more Smart Citations

Improving User Experience of Virtual Health Assistants: Scoping Review

Curtis¹,

Bartel²,

Ferguson³

et al. 2021

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…The importance of incorporating humor into computational dialogue models of human computer interaction has been made before [22], [23], [24], However, due to the intricate nature of human conversational interaction and given the many prevalent and commonly made erroneous assumptions about the nature and function of human communication-some of which are outlined at the start of this paper-there has been little incorporation of humor into dialogues that occur in real-time and that can flow-freely. Most dialogues models are constrained to fixed scenarios or involve tasks such as information provision that are highly functional in nature.…”

Section: Implications For Computational Models Of Humormentioning

confidence: 99%

Humor as an Ostensive Challenge that Displays Mind-Reading Ability

McKeown

2017

Distributed, Ambient and Pervasive Interactions

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Understanding humor in human social interaction is a prerequisite to the creation of engaging interactions between humans and digital assistants, embodied conversational agents and social robots. As these HCI methods become more prevalent and pervasive, more advanced conversational discourse abilities will be required. However, many models of dialogue and human communication used in computer science remain based upon outdated understanding of the manner in which humans communicate with one another. This paper addresses these issues introducing a view of communication based on Relevance theory and the Analogical Peacock Hypothesis in which humor and humorous interactions are viewed as ostensive challenges inviting the receiver of a communication to engage in greater levels of cognitive processing and effort to resolve the challenge set by a humorous display. The increased effort is rewarded with positive socio-cognitive effects-a humorous payoff and knowledge of the mind-reading abilities of the humor producer.

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