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152 results for “chatbot”
A Study Evaluating Sleep, Stress and Infant Nutrition Using a Chatbot
ClinicalTrials.gov study NCT03630679. IPD Sharing: NO. Countries: 1. Publications: 1.
Can Mental Health Chatbots Help Chronic Disease Populations?
ClinicalTrials.gov study NCT04620668. IPD Sharing: NO. Countries: 1. Publications: 6.
Step Away: Comparing a Chatbot-delivered Alcohol Intervention With a Smartphone App
ClinicalTrials.gov study NCT04447794. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Artificial Intelligence (AI) Technology May Help Patients to Understand Bowel Preparation Better Before They go for Colonoscopy.This Study Attempts to Leverage AI Chatbot in Counselling Patients to Im
ClinicalTrials.gov study NCT06905782. IPD Sharing: YES. Countries: 1. Publications: 1.
Evaluating the Effectiveness and Acceptability of a GPT-4o and RAG-Based Voice Chatbot for Depression Screening Using PHQ-9
ClinicalTrials.gov study NCT06801925. IPD Sharing: NO. Countries: 1. Publications: 0.
Can a Smartphone App That Includes a Chatbot-based Coaching and Incentives Increase Physical Activity in Healthy Adults?
ClinicalTrials.gov study NCT03384550. IPD Sharing: YES. Countries: 1. Publications: 2.
Data for: A behaviourally-informed chatbot increases vaccination in Argentina
Open the record for dataset details and reuse information.
UCI Libraries chatbot Transcripts (ANTswers)
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Package for the paper Unveiling Assumptions: Exploring the Decisions of AI Chatbots and Human Testers
<p>This package includes the data for the study reported in the paper "Unveiling Assumptions: Exploring the Decisions of AI Chatbots and Human Testers".</p> <p>The data includes (i) answers from 127 human testers on a simple test prioritisation problem, (ii) answers from four chatbots prompted with the same problem (ChatGPT 4 and 3.5, Bard and Copilot), and (iii) scripts to create plots and tables used in the paper.</p> <p>Intructions about using the paper are in the README.md file.</p>
Experimental dataset on the effects of guidelines in experimental studies of educational chatbots
<p>This dataset comprises materials and collected data from an experiment to understand the effects of the use of guidelines for mitigating<br>threats in experimental studies of educational. The materials include characterization forms, experimentation guidelines, presentation slides, Informed Consent Forms (ICFs), experimental design templates, and activity descriptions for participants. The collected data encompass experimentation results, participant feedback, and analyses on the efficacy of the guidelines in enhancing the design and performance of educational chatbots.</p>
Mutation Testing for Task-Oriented Chatbots: Dataset
<p>Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.</p> <p>To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.</p>
Optimizing Artificial Intelligence (AI) Chatbot Customer Service in Small and Medium Enterprises (SMEs) in E-Marketplace
<p><span>The rise of advanced technologies, such as AI- driven chatbots, enables SMEs in e-marketplaces to provide responsive and efficient customer support, improve engagement, and streamline services. However, customers increasingly express concerns about AI-supported chatbot services, which affects their willingness to engage with these technologies. Consequently, this study aims to examine the factors<span> </span>that<span> </span>influence<span> </span>customers'<span> </span>behavioral<span> </span>intentions<span> </span>to<span> </span>use<span> </span>AI and their intentions for the continued use of AI-supported chatbots. Using a purposive sampling technique, the study collected data from 152 respondents through an online questionnaire. To analyze and predict the findings from the collected data, the study employed PLS-SEM as its statistical approach. The<span> </span>results<span> </span>indicate<span> </span>that<span> </span>information<span> </span>quality, system quality, and service quality significantly influence trust. Furthermore, service quality, perceived ease of use, confirmation of expectations, and perceived usefulness affect user satisfaction. Additionally, confirmation of expectations impacts perceived usefulness, and user satisfaction influences the behavioral intention to use AI chatbots. The findings also reveal that trust, user satisfaction, and perceived usefulness effectively enhance the intention to continue using AI-driven chatbots. However, information quality and system quality do not correlate with user satisfaction, and confirmation of expectations does not relate to<span> </span>user satisfaction. These findings contribute valuable insights to the existing literature on AI- driven chatbot services. Furthermore, stakeholders involved with AI-driven chatbot services for SMEs will gain an understanding<span> </span>of<span> </span>how<span> </span>to<span> </span>enhance<span> </span>user-friendly<span> </span>chatbot<span> </span><span>services.</span></span></p>
A Transformer-based Approach for Augmenting Software Engineering Chatbots Datasets
<p>The results, datasets, and scripts used in "A Transformer-based Approach for Augmenting Software Engineering Chatbots Datasets" paper.</p>
Artificial intelligence as a company's internal communication media: Investigating employee's acceptance of chatbot for effective communication and sustainable business
<p><span><span>This research investigates Kalbe Consumer Health (KCH) employees’ acceptance of AMBER, a Generative AI Chatbot implemented at KCH. KCH, a prominent pharmaceutical company with over 27 years of experience, has been recognized as the best place to work in Asia for two consecutive years by HR Asia. Despite its success, challenges persist, by the end of 2022, it has reached a 5 percent turnover rate with 70 percent departures in leadership positions. AMBER is an internal communication tool, functioning for employees to express their sentiments and opinions honestly. </span></span><span>By fostering an environment where employees feel heard and valued, AMBER encourages proactive issue resolution within teams.</span><span><span> Drawing </span></span><span>on the Uses and Gratification Theory (UGT) and the Unified Theory of Acceptance and Use of Technology (UTAUT), this study employs regression analysis to analyze data from an anonymous online survey. </span><span><span>The study contributes theoretically by integrating UGT and UTAUT into the context of chatbot utilization in internal communication. Furthermore, it offers practical insights for businesses leveraging AI in communication strategies, facilitating sustainable business practices, and aligning with Sustainable Development Goals (SDG) 16 and 8 by fostering an inclusive, transparent, and accountable culture, and enhancing employee satisfaction and performance through effective communication.</span></span></p>
Supplementary Material for Human Factors in the Design of Chatbot Interactions: Conversational Design Practices
<p>Supplementary Material for the thesis entitled <em>Human Factors in the Design of Chatbot Interactions: Conversational Design Practices.</em></p> <p>This repository contains the following files<em>:</em></p> <ul> <li><em>systematic_literature_review_data -> </em>Dataset of the retrieved papers from the SLR, the indication of papers that were removed at each step of the protocol, the list of accepted papers, and the search strings that were used;</li> <li><em>guide_vX -> </em>Faithful prints of the guide's web pages that were shared with the validation participants. V1 was used in the survey, V2 was used in the case study, and V3 is the final version;</li> <li><em>validation_survey</em> -> <ul> <li>A copy of the Google Forms questionnaire that was used in the survey;</li> <li>Sheet with the answers to this survey;</li> </ul> </li> <li><em>validation_case_study</em> -> <ul> <li><em>conversation_samples -> </em>Conversations made by the participants in the case study stages. In each file, the conversation from the left was made without the guide, and the one from the right was created with the guide;</li> <li><em>interview_transcripts -> </em>Transcripts of the interviews conducted with each participant at the last stage of the case study;</li> <li><em>instructions_to_participants.pdf</em> -> File provided to participants containing the instructions for each step of the case study;</li> <li><em>transcripts_coding.xlsx -> </em>Sheet containing transcripts from participants' responses and the corresponding code after the thematic analysis;</li> </ul> </li> </ul>
The Impact of an Artificial Intelligence Chatbot on Brazilian Adolescents' Body Image
ClinicalTrials.gov study NCT04825184. IPD Sharing: NO. Countries: 1. Publications: 12.
Effects of a Visual Interactive LINE Chatbot on Self-Management of EGFR-TKI Related Side Effects in Patients With Lung Cancer
ClinicalTrials.gov study NCT07310589. IPD Sharing: YES. Countries: 0. Publications: 4.
Using Artificial Intelligence-based ChatBot to Improve Women's Participation to Cervical Cancer Screening Programme
ClinicalTrials.gov study NCT05286034. IPD Sharing: NO. Countries: 1. Publications: 1.
The MARVIN Chatbots to Provide Information for Different Health Conditions
ClinicalTrials.gov study NCT05789901. IPD Sharing: NO. Countries: 1. Publications: 1.
The Effectiveness of a Chatbot-facilitated High Alert Medication Education for 2-year Post Graduate Nurses
ClinicalTrials.gov study NCT05985005. IPD Sharing: YES. Countries: 1. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.