COVID-19
In order to explore the influencing factors of college students' learning intention on online teaching video during the pandemic, this article uses empirical research on college students from four aspects including performance expectancy, effort expectancy, social influence and facilitating conditions.
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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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COVIDSentiRO contains 19319 Romanian tweets extracted in the time-frame 01.01.2021 - 28.02.2022 using query words related to COVID-19 vaccination. Each tweet has its timestamp associated and is labelled with positive, negative and neutral, using the SART dataset for sentiment analysis.
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The problem of effective disposal of the trash generated by people has rightfully attracted major interest from various sections of society in recent times. Recently, deep learning solutions have been proposed to design automated mechanisms to segregate waste. However, most datasets used for this purpose are not adequate. In this paper, we introduce a new dataset, TrashBox, containing 17,785 images across seven different classes, including medical and e-waste classes which are not included in any other existing dataset.
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The dataset is about some real epidemic networks of covid19.
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<p>This multilingual Twitter dataset spans over 2 years from October 2019 to the end of 2021, including 3 months before the outbreak of the COVID-19 pandemic.</p>
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This dataset includes (i) mental health and emotional wellbeing; (ii) factors / stressors in the work environment; (iii) organizational and social support; (iv) personal characteristics; and, (v) demographics.
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