UX Research on Conversational Human-AI Interaction: A Literature Review of the ACM Digital Library

Zheng, Qingxiao; Tang, Yiliu; Liu, Yiren; Liu, Weizi; Huang, Yun

doi:10.1145/3491102.3501855

Cited by 32 publications

(5 citation statements)

References 152 publications

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“…Recent work explored the feasibility of using CA to help increase the effectiveness and efficiency of collecting evidential statements from both victims and witnesses [Minhas et al(2022)]. Our findings also contributed to the growing body of evidence that a conversational agent tool can be created to increase communication consistency and efficiency by facilitating interactions between users and dispatchers [Zheng et al(2022)]. The CA might improve service quality by supporting dispatchers in producing better reply messages, which would increase users' responsiveness.…”

Section: Designing Conversational Agents For High-quality Reportingmentioning

confidence: 73%

Discovering the Hidden Facts of User-Dispatcher Interactions via Text-based Reporting Systems for Community Safety

Liu¹,

Mayfield²,

Huang³

2022

Preprint

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Recently, an increasing number of safety organizations in the U.S. have incorporated text-based risk reporting systems to respond to safety incident reports from their community members. To gain a better understanding of the interaction between community members and dispatchers using text-based risk reporting systems, this study conducts a system log analysis of LiveSafe, a community safety reporting system, to provide empirical evidence of the conversational patterns between users and dispatchers using both quantitative and qualitative methods. We created an ontology to capture information (e.g., location, attacker, target, weapon, start-time, and end-time, etc.) that dispatchers often collected from users regarding their incident tips. Applying the proposed ontology, we found that dispatchers often asked users for different information across varied event types (e.g., Attacker for Abuse and Attack events, Target for Harassment events). Additionally, using emotion detection and regression analysis, we found an inconsistency in dispatchers' emotional support and responsiveness to users' messages between different organizations and between incident categories. The results also showed that users had a higher response rate and responded quicker when dispatchers provided emotional support. These novel findings brought significant insights to both practitioners and system designers, e.g., AI-based solutions to augment human agents' skills for improved service quality.

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Section: Designing Conversational Agents For High-quality Reportingmentioning

confidence: 73%

Discovering the Hidden Facts of User-Dispatcher Interactions via Text-based Reporting Systems for Community Safety

Liu¹,

Mayfield²,

Huang³

2022

Preprint

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“…It could be useful to deepen the research with other methods, both quantitative and qualitative. We are thinking about developing UX research (Barnum, 2019;Zheng et al, 2022) and cyberethnography (Ward, 1999), giving a more profound interpretation of the present results and suggesting new directions for research. design of the concept of the article.…”

Section: Discussionmentioning

confidence: 87%

Contributions of digital social research to develop Telemedicine in Calabria (Southern Italy): identification of inequalities in post-COVID-19

Taddei,

Mendicino,

Grande

et al. 2023

Front. Sociol.

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The paper discusses the role that sociology and digital social research methods could play in developing E-health and Telemedicine, specifically after the COVID-19 pandemic, and the possibility of dealing with new pandemics. In this article, we will reflect on an interdisciplinary research pilot project carried out by a team of sociologists, medical doctors, and software engineers at The University of Calabria (Italy), to give a proof of concept of the importance to develop Telemedicine through the contribution of digital social research. We apply a web and app survey to administrate a structured questionnaire to a self-selected sample of the University Community. Digital social research has highlighted socioeconomic and cultural gaps that affect the perception of Telemedicine in the University Community. In particular, gender, age, educational, and professional levels influence medical choices and behaviors during Covid-19. There is often an unconscious involvement in Telemedicine (people use it but don't know it is Telemedicine), and an optimistic perception grows with age, education, professional, and income levels; equally important are the comprehension of digital texts and the effective use of Telemedicine. Limited penetration of technological advances must be addressed primarily by overcoming sociocultural and economic barriers and developing knowledge and understanding of digital environments. The key findings of this study could help direct public and educational policies to reduce existing gaps and promote Telemedicine in Calabria.

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“…AI chatbots use the help of machine learning algorithms that allow chatbots to learn new things. AI chatbots can carry out conversations better than rule-based chatbots because they use machine learning algorithms, NLP, and sentiment analysis [64]. Machine learning chatbots allow identifying user input.…”

Section: Chatbot In Educationmentioning

confidence: 99%

Natural Language Processing in Higher Education

Putri,

Widiharso,

Utama

et al. 2023

Bull.Socinf.The.App

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The application of Natural Language Processing (NLP) in an educational institution is still quite broad in its scope of use, including the use of NLP on chatterbots for academic consultations, handling service dissatisfaction, and spam email detection. Meanwhile, other uses that have not been widely used are the combination of NLP and Global Positioning Satellite (GPS) in finding the location of lecture buildings and other facilities in universities. The combination of NLP and GPS is expected to make it easier for new students, as well as visitors from outside the university, to find the targeted building and facilities more effectively.

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UX Research on Conversational Human-AI Interaction: A Literature Review of the ACM Digital Library

Cited by 32 publications

References 152 publications

Discovering the Hidden Facts of User-Dispatcher Interactions via Text-based Reporting Systems for Community Safety

Discovering the Hidden Facts of User-Dispatcher Interactions via Text-based Reporting Systems for Community Safety

Contributions of digital social research to develop Telemedicine in Calabria (Southern Italy): identification of inequalities in post-COVID-19

Natural Language Processing in Higher Education

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