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【目的】深入了解埃博拉事件中科技期刊所承担的社会责任。【方法】 对中国知网(CNKI)上发表的所有篇名中含有埃博拉的论文进行统计分析,来源数据库为"中国学术期刊网络出版总库",检索结果使用Microsoft Office 2007 Excel进行整理和统计。检索截止时间为2015年7月15日。【结果】 自1995年至今20年间,共有150种科技期刊发表了579篇有关埃博拉的论文,其中以2014年发表的论文数量最多(259篇),占总发文量的44.7%。发文量与疫情暴发的年份基本吻合。【结论】 从分析结果可见,作为承载着科学传播任务的科技期刊,对此次埃博拉事件高度关注,从多方面、多角度进行了深层次的报道。 相似文献
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【目的/意义】网络舆情预警作为反映社会舆情的“晴雨表”和“提示器”,有助于政府部门通过公告、沟通、情
绪安慰和教育活动对社会进行科学管理。【方法/过程】本文基于Python数据爬虫技术,将刚果（金）赤道省疫情期间
的 38天分为 38个时间点,进一步构造 SVM 模型,并用 Matlab对 SVM 模型进行训练。其中 5月 18日至 6月 18日数
据为训练样本,6月19日至6月25日数据为检验样本。【结果/结论】通过实证研究,危机程度大于和小于0.5的情况
均合理有效,预警模型实用性强,对政府、社会、媒体应对危机产生了较大价值。【创新/局限】但由于本研究仅是针
对埃博拉展开,从Twitter中获取的数据量有限,因此存在一定研究局限性。未来将尝试选择基于更多的主题,从多
个来源提取更多数据,以对网络舆情危机预警机制进行更加系统、全面地研究。 相似文献
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Using nine Demographic and Health Surveys for the three West African countries affected by the 2013−16 Ebola epidemic, this study applies a district-level interrupted time series (ITS) design to explore the longer-term impacts of the epidemic on school attendance. It shows that, about three to four years after the crisis, attendance has returned to the long-term trend regardless of the difference in Ebola virus disease prevalence among districts. The study also shows no discernable effect on the attendance trends for children from vulnerable backgrounds. However, it suggests further areas for examination and study. This includes migration patterns, the investment of emergency relief and overseas development aid between regions, the possible role of orphan status and early marriage (for girls) as vectors for the effect of the EVD crisis on educational outcomes and learnings losses for children who were out of school for up to an entire school year. 相似文献
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This study investigates how nonprofit organizations use hyperlinks embedded in tweets for strategic communication during global health crises. Within the 1,494 links included in tweets about Ebola, organizations shared owned and earned media, including news stories directly or indirectly referencing their work and positive mentions from others on social media. Links allowed organizations to raise awareness about Ebola in West Africa, promote their work, and highlight endorsements from news media and influential users. Raising awareness and building trust are key steps in becoming credible sources during highly uncertain crises. 相似文献
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Brittani Crook Elizabeth M. Glowacki Melissa Suran Jenine K. Harris Jay M. Bernhardt 《Communication Research Reports》2016,33(4):349-355
A public response to a looming health threat may be marked with misinformation and panic. However, providing the public with accurate information and updates may be an effective way to prevent widespread fear. In response to the 2014 Ebola panic in the United States, the U.S. Centers for Disease Control and Prevention (CDC) initiated a Twitter conversation with the public to alleviate concerns and provide accurate information about the disease. This study conducted a content analysis of 512 randomly selected tweets by the general public directed to the CDC. The major themes identified included the etiology of Ebola, policy, the environment, spread and scope of the disease, fear and anxiety from the public, and misinformation. Practical implications of these findings include encouraging government and emergency health response organizations to prepare educational messages and materials in advance that detail responses to common questions, such as transmission and symptoms. 相似文献
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P. Sean Smith Jennifer A. Torsiglieri R. Keith Esch Joan D. Pasley 《International Journal of Science Education》2013,35(13):1830-1845
ABSTRACTThe tension between mandated curricula and students’ interests is evident throughout the history of science education. Societal expectations for student learning often lead to standards and curricula that leave little room for students to explore their own individual interests. Occasionally, however, an event can capture the interest of so many students that teachers feel compelled to respond. The Ebola outbreak of 2014 was such an event. This article discusses findings from a study of teacher decision-making; specifically, it explores how high school science teachers in the U.S. decided whether and how they should address Ebola during the 2014–2015 school year, when the Ebola outbreak in West Africa was at its peak. Approximately 2500 teachers of science responded to an online questionnaire that addressed their Ebola-specific instruction. In comparing the decisions of those who taught about Ebola and those who did not, the study found that teachers weighed various factors, in particular student interest but also curriculum standards, time, and availability of resources for teaching about Ebola. The article concludes with implications for future urgent health-related issues. 相似文献
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Jie Shen 《Interactive Learning Environments》2019,27(3):288-292
Excellent film is an integrated art. It has rich knowledge and profound ideological connotations. In order to promote students’ enthusiasm for learning about biology, we made some attempts on how to use movie clips for biological teaching and achieved good results. Making use of movie’s sound, color, light, and animations, we tried to enrich students’ perceptions from multiple perspectives and help students understand abstract concepts. Therefore, this paper proposes the idea of eliciting positive emotions by showing students movie clips to enhance their understanding of the Ebola virus infection process. 相似文献
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Unstructured tweet feeds are becoming the source of real-time information for various events. However, extracting actionable information in real-time from this unstructured text data is a challenging task. Hence, researchers are employing word embedding approach to classify unstructured text data. We set our study in the contexts of the 2014 Ebola and 2016 Zika outbreaks and probed the accuracy of domain-specific word vectors for identifying crisis-related actionable tweets. Our findings suggest that relatively smaller domain-specific input corpora from the Twitter corpus are better in extracting meaningful semantic relationship than generic pre-trained Word2Vec (contrived from Google News) or GloVe (of Stanford NLP group). However, domain-specific quality tweet corpora during the early stages of outbreaks are normally scant, and identifying actionable tweets during early stages is crucial to stemming the proliferation of an outbreak. To overcome this challenge, we consider scholarly abstracts, related to Ebola and Zika virus, from PubMed and probe the efficiency of cross-domain resource utilization for word vector generation. Our findings demonstrate that the relevance of PubMed abstracts for the training purpose when Twitter data (as input corpus) would be scant during the early stages of the outbreak. Thus, this approach can be implemented to handle future outbreaks in real time. We also explore the accuracy of our word vectors for various model architectures and hyper-parameter settings. We observe that Skip-gram accuracies are better than CBOW, and higher dimensions yield better accuracy. 相似文献
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