论文标题
使用Altmetrics检测准Zero-day时期的有影响力的研究:COVID-19
Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19
论文作者
论文摘要
2019年12月31日,世界卫生组织(WHO)中国国家办公室被告知武汉市检测到的未知病因的肺炎病例。该综合征的原因是一种新型的冠状病毒,于2020年1月7日分离,被称为严重的急性呼吸综合症冠状病毒2(SARS-COV-2)。 SARS-CoV-2 is the cause of the coronavirus disease 2019 (COVID-19). Since January 2020 an ever increasing number of scientific works have appeared in literature. Identifying relevant research outcomes at very early stages is challenging. In this work we use COVID-19 as a use-case for investigating: (i) which tools and frameworks are mostly used for early scholarly communication; (ii) to what extent altmetrics can be used to identify potential impactful research in tight (i.e. quasi-zero-day) time-windows.在文献中,在文献中出现了由有关SARS-COV-2/COVID-19的科学论文组成的样本的文献综述,以收集有关SARS-COV-2/COVID-19的样本,在2020年1月15日至2020年2月24日的紧缩窗口中出现在文献中。该样本用于构建有关论文和指标的知识图表。该知识图为数据分析过程提供了用于使用Altmetrics作为影响指标的数据分析过程。我们发现传统的引文数量,社交媒体上的引用以及新闻和博客提及之间的相关性。 This suggests there is a common intended meaning of the citational acts associated with aforementioned indicators.此外,我们定义了一种和谐指标以提供多维影响指标的方法。
On December 31st 2019, the World Health Organization (WHO) China Country Office was informed of cases of pneumonia of unknown etiology detected in Wuhan City. The cause of the syndrome was a new type of coronavirus isolated on January 7th 2020 and named Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2). SARS-CoV-2 is the cause of the coronavirus disease 2019 (COVID-19). Since January 2020 an ever increasing number of scientific works have appeared in literature. Identifying relevant research outcomes at very early stages is challenging. In this work we use COVID-19 as a use-case for investigating: (i) which tools and frameworks are mostly used for early scholarly communication; (ii) to what extent altmetrics can be used to identify potential impactful research in tight (i.e. quasi-zero-day) time-windows. A literature review with rigorous eligibility criteria is performed for gathering a sample composed of scientific papers about SARS-CoV-2/COVID-19 appeared in literature in the tight time-window ranging from January 15th 2020 to February 24th 2020. This sample is used for building a knowledge graph that represents the knowledge about papers and indicators formally. This knowledge graph feeds a data analysis process which is applied for experimenting with altmetrics as impact indicators. We find moderate correlation among traditional citation count, citations on social media, and mentions on news and blogs. This suggests there is a common intended meaning of the citational acts associated with aforementioned indicators. Additionally, we define a method that harmonises different indicators for providing a multi-dimensional impact indicator.