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The outbreak of the COVID-19 pandemic has created significant challenges for people worldwide. To combat the virus, one of the most dramatic measures was the lockdown of 4 billion people in what is believed to be the largest quasi-quarantine in human history. As a response to the call to study information behavior during a global health crisis, we adopted a resource orchestration perspective to investigate six Chinese families who survived the lockdown. We explored how elderly, young and middle-aged individuals and children resourced information and how they adapted their information behavior to emerging online technologies. Two information resource orchestration practices (information resourcing activities and information behavior adaptation activities) and three mechanisms (online emergence and convergence in community resilience, the overcoming of information flow impediments, and the application of absorptive capacity) were identified in the study.  相似文献   
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This study examined the impact of the COVID-19-induced school lockdown on need satisfaction, well-being and motivation in both gifted and non-gifted primary school students in the Netherlands. A total of 312 parents (122 from gifted children) participated. The lockdown had mainly negative effects on students' need satisfaction, well-being and motivation. However, the impact of the lockdown was less negative for gifted students. There was also a levelling effect: Before the lockdown, gifted students had lower need satisfaction, well-being and motivation than their non-gifted peers, but these differences decreased during the lockdown due to (stronger) declines in the non-gifted. Changes in non-gifted students' well-being and motivation, because of the lockdown, were negatively mediated by autonomy and relatedness with classmates. Among the gifted, this was positively mediated by competence. Only before the lockdown, the effects of giftedness on well-being and motivation were mediated by autonomy and relatedness satisfaction.  相似文献   
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As COVID-19 swept over the world, people discussed facts, expressed opinions, and shared sentiments about the pandemic on social media. Since policies such as travel restriction and lockdown in reaction to COVID-19 were made at different levels of the society (e.g., schools and employers) and the government, we build a large geo-tagged Twitter dataset titled UsaGeoCov19 and perform an exploratory analysis by geographic location. Specifically, we collect 650,563 unique geo-tagged tweets across the United States covering the date range from January 25 to May 10, 2020. Tweet locations enable us to conduct region-specific studies such as tweeting volumes and sentiment, sometimes in response to local regulations and reported COVID-19 cases. During this period, many people started working from home. The gap between workdays and weekends in hourly tweet volumes inspire us to propose algorithms to estimate work engagement during the COVID-19 crisis. This paper also summarizes themes and topics of tweets in our dataset using both social media exclusive tools (i.e., #hashtags, @mentions) and the latent Dirichlet allocation model. We welcome requests for data sharing and conversations for more insights.UsaGeoCov19 link: http://yunhefeng.me/geo-tagged_twitter_datasets/.  相似文献   
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