Social Sciences
Replication data for the fsQCA model in: "Why do companies employ prohibited unethical artificial intelligence practices?"
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The dataset analyzed in this study is the result of a systematic literature review and a crowdsourced mini-project that aimed to identify and validate metrics relevant to maternal and neonatal healthcare examinations. The study involved a diverse group of participants, including 193 registered medical personnel from reputable institutions and 161 non-medical individuals who were active on various social media platforms related to maternal and neonatal healthcare.
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Cars, mobile phones, and smart home devices already provide automatic speech recognition (ASR) by default. However, human machine interfaces (HMI) in industrial settings, as opposed to consumer settings, operate under different conditions and thus, present different design challenges. Voice control, arguably the most natural form of communication, has the potential to shorten complex command sequences and menu structures in order to directly execute a final command.
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This dataset (MegaGeoCOV Extended), which is an extended version of MegaGeoCOV, was introduced in this paper: A Twitter narrative of the COVID-19 pandemic in Australia (the paper will appear in proceedings of the 20th ISCRAM conference, Omaha, Nebraska, USA May 2023). Please refer to the paper for more details (e.g., keywords and hashtags used, descriptive statistics, etc.).
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The purpose of this manuscript was to study the global structure of standards in the development of regularly published scientific articles. Writers and new researchers can improve their scientific writing skills by using measurable guidelines that are easy to learn by all circles, including non-scientific readers. Furthermore, this article was created using the second reading source adopted from the (department of psychology, 2023).
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A viewer's existing beliefs can prevent accurate reasoning with data visualizations. In particular, confirmation bias can cause people to overweigh information that confirms their beliefs, and dismiss information that disconfirms them. We tested whether confirmation bias exists when people reason with visualized data and whether certain visualization designs can elicit less biased reasoning strategies. We asked crowdworkers to solve reasoning problems that had the potential to evoke both poor reasoning strategies and confirmation bias.
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BillionCOV is a global billion-scale English-language COVID-19 tweets dataset with more than 1.4 billion tweets originating from 240 countries and territories between October 2019 and April 2022. This dataset has been curated by hydrating the 2 billion tweets present in COV19Tweets.
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This dataport will be useful to those interested in visual design for complex physics phenomena. We have included two quantum physics data sample datasets and our empirical study results.
(1) evaluation results from two experiments (20 participants in each and 40 in total) to empirically validate that separable bivariate pairs of large-magnitude-range vector
magnitude representations are more efficient than integral pairs.
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Gestational diabetes is a type of high blood sugar that develops during pregnancy. It can occur at any stage of pregnancy and cause problems for both the mother and the baby, during and after birth. The risks can be reduced if they are early detected and managed, especially in areas where only periodic tests of pregnant women are available. Intelligent systems designed by machine learning algorithms are remodelling all fields of our lives, including the healthcare system. This study proposes a combined prediction model to diagnose gestational diabetes.
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