A text-messaging chatbot to support outdoor recreation monitoring through community science

Lia, Emilia H.; Derrien, Monika M.; White, Eric M.; Winder, Samantha G.; Wood, Spencer A.

doi:10.1016/j.diggeo.2023.100059

Cited by 5 publications

(1 citation statement)

References 48 publications

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“…[33] discussed the significance of AI and 3D technology in strategies for the energy sector. Chatbots have also been combined with intelligent data collection technologies to monitor outdoor recreational activities [34].…”

Section: Multidisciplinary Application Of Chatbotsmentioning

confidence: 99%

Empirical Assessment of User Satisfaction with American and Chinese AI Chatbots

Wang,

Lin,,

Huang,

et al. 2023

ijmst

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As artificially intelligent chatbots grow in popularity, exploring user satisfaction has become an important topic. This study deviates from the conventional questionnaire approach by adopting a balanced paired design. We employed 40 users to participate in usability testing to assess their satisfaction with the responses of two prominent chatbots (ChatGPT 4.0 from the US and inChat from China) over five domains (daily life, the workplace, advertising copy, current affairs commentary, and translation). We conducted a comparative analysis based on three demographic variables: gender, experience with chatbots, and generation (i.e., age). Empirical results revealed that the participants were more satisfied with inChat's responses overall and for daily life scenarios in particular than with those of ChatGPT 4.0. Further, female participants expressed higher satisfaction with inChat's commentary on current affairs than did male participants. Prior use of chatbots did not significantly influence satisfaction levels; however, Baby Boomers (i.e., those born between 1946 and 1964) showed a notably higher appreciation for inChat's translation capabilities and higher satisfaction overall compared to Generation Y (i.e., those born between 1981 and 1996).

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Section: Multidisciplinary Application Of Chatbotsmentioning

confidence: 99%

Empirical Assessment of User Satisfaction with American and Chinese AI Chatbots

Wang,

Lin,,

Huang,

et al. 2023

ijmst

View full text Add to dashboard Cite

show abstract

Designing a conversational agent for supporting data exploration in citizen science

Stein,

Teubner,

Morana

2024

Electron Markets

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Data is ubiquitous in today’s digitized society. However, access to and literacy in handling data plays a pivotal role in determining who can benefit from it and who can use—or potentially misuse—it. To combat inequalities and address issues such as misinformation, it is essential to enable citizens to effectively access and understand data within their local ecosystems. To address this challenge, we focus on the case of citizen science and propose using a conversational agent to support data exploration and lower barriers to citizen engagement in research projects. Using a design science research approach, we derive design principles and develop a prototypical artifact. Moreover, we conduct an experimental evaluation, demonstrating strong interest among citizens to participate in scientific data analysis and that conversational agents hold great potential in increasing data literacy.

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