Incorporating Multimodal Sentiments into Conversational Bots for Service Requirement Elicitation

Yu, Dan; Tian, Junrui; Su, Tonghua; Tu, Zhiying; Xu, Xiaofei; Wang, Zhongjie

doi:10.1109/sose52839.2021.00014

Cited by 6 publications

(4 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The valence dimension categorizes emotions as positive or negative ( Izard, 1991 ). Studies ( Sutcliffe, 2011 ; Jiang & Li, 2020 ; Thew & Sutcliffe, 2018 ; Abdullah et al , 2020 ; Yeewai et al, 0000 ; Stade et al, 2019 ; Levy, 2020 ; Zhou, Jianxin Jiao & Linsey, 2015 ; Mulvenna et al, 2017 ; Levy, 2020 ; Maier & Berry, 2017 ; Sutcliffe, 2012 ; Cheng et al, 2023 ; Bolchini, Garzotto & Paolini, 2007 ; Thew & Sutcliffe, 2008 ; Curumsing et al, 2015 ; Yu et al, 2021 ) underscore considering emotion valence in requirements engineering, product design, and user experience. Analyzing valence provides insight into the potential impact of emotions on users.…”

Section: Resultsmentioning

confidence: 99%

“…Content analysis of interviews, surveys, and trials combined with affinity diagrams and goal modeling has elicited smart home users’ emotional goals ( Curumsing et al, 2019 ). Conversational agents with multimodal sentiment analysis capabilities have been proposed to recognize user intentions and gather service requirements ( Yu et al, 2021 ). Focus groups and storytelling have been used in a participatory design approach to elicit requirements from users with specialized needs, like people with dementia ( Mulvenna et al, 2017 ).…”

Section: Resultsmentioning

confidence: 99%

“…Only 9% of studies utilized experiments to empirically verify the proposed methods. For example, ( Yu et al, 2021 ) conducted a controlled experiment using a conversational AI bot integrated with multimodal sentiment analysis to validate the effectiveness of incorporating sentiments for user intention mining.…”

Section: Resultsmentioning

confidence: 99%

“…The approach proposed in Abdullah et al (2020) can capture emotional goals relating to different roles interacting with the system. Another approach considered improved user experience by recognizing user emotions and developing user-friendly conversational AI bots ( Yu et al, 2021 ). To help users express emotions and address challenges in describing emotions, an approach was proposed using a circumplex model built on valence and arousal dimensions ( Alkhomsan, Baslyman & Alshayeb, 2022 ).…”

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

Eliciting and modeling emotional requirements: a systematic mapping review

Alkhomsan,

Baslyman,

Alshayeb

2024

PeerJ Computer Science

View full text Add to dashboard Cite

Context Considering users’ emotions plays an extremely crucial role in the adoption and acceptance of recent technology by the end user. User emotions can also help to identify unknown requirements, saving resources that would otherwise be wasted if discovered later. However, eliciting and modeling users’ emotional requirements in software engineering is still an open research area. Objective This systematic mapping review analyzes emotional requirements (ER) practices in software engineering from two perspectives: elicitation and modeling. For elicitation techniques, we investigate the techniques, evaluation methods, limitations, and application domains. For modeling techniques, we examine the modeling languages, analyses, limitations, and domains. Method We systematically reviewed studies on emotional requirements engineering published between 1993–2023 and identified 46 relevant primary studies. Results A total of 34 studies investigated ER elicitation techniques, five examined modeling techniques, and seven covered both. Illustrative case studies were the main evaluation method for proposed elicitation techniques. Identified limitations include time consumption and extensive human involvement. The dominant application domains were healthcare and well-being, and game development. Conclusion This review summarizes the current landscape of emotional requirements research, highlighting key elicitation and modeling techniques, evaluations, limitations, and domains. Further research can build on these findings to advance emotional requirements practices in software engineering. Future research may address (1) managing conflicting emotional requirements across users, (2) evaluating the value and impact of considering emotional requirements during the development and (3) Modeling and analyzing emotional requirements in relation to other requirements.

show abstract