REALM: An Altmetrics-based Framework to Map Science Impacts on Society. A Case Study on Zika Research

Luís Fernando Monsores Passos Maia, M. Lenzi, E. Rabello, Jonice Oliveira
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引用次数: 4

Abstract

Nowadays, a lot of universities and research institutes are concerned with measuring their scientists’ productivity and the public awareness of its scientific discoveries, that is, how citizens interpret the efficiency of scientists and their efforts to find solutions. This scenario demands mechanisms to identify the experts’ reputation in specific domains or topics of interest, such as the Zika epidemic. In this paper we describe an altmetrics-based framework which allows the identification of specialists and important research in specific research scenarios. Besides, we did an implementation of the framework and applied it in the Zika scenario where the most important names and disease-related studies were identified and their public awareness was analysed via altmetrics.CCS Concepts• Networks $\rightarrow$ Online social networks; • Human-centered computing $\rightarrow$ Social network analysis; Reputation systems.
REALM:一个基于替代度量的框架来描绘科学对社会的影响。寨卡病毒研究个案研究
如今,许多大学和研究机构关心的是衡量他们的科学家的生产力和公众对其科学发现的认识,也就是说,公民如何解释科学家的效率和他们寻找解决方案的努力。这种情况需要建立机制,以确定专家在特定领域或感兴趣的主题(如寨卡疫情)中的声誉。在本文中,我们描述了一个基于替代度量的框架,它允许在特定的研究场景中识别专家和重要的研究。此外,我们对该框架进行了实施,并将其应用于寨卡病毒方案,确定了最重要的名称和与疾病相关的研究,并通过altmetrics分析了它们的公众意识。CCS Concepts•Networks $\右箭头$在线社交网络;•以人为本的计算$\右箭头$社会网络分析;声誉系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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