The purpose of this paper is to examine the classic characteristics of highly cited articles (HCAs) of top-ranked library and information science (LIS) journals and get acquainted with the high-quality works in specific areas of LIS for distinguishing what gets cited and who the prolific authors are.,The HCAs published across the top four LIS journals were downloaded, coded and a database was developed with basic metadata elements for analysis using bibliometric indicators. Lotka’s Inverse Square Law of Scientific Productivity was applied to assess the author’s productivity of HCA. The content analysis method was also used to find out the emerging areas of research that have sought high citations.,Inferences were drawn for the proposed five number of research questions pertaining to individual productivity, collaboration patterns country and institutional productivity, impactful areas of research. The Netherland found to be the potential player among all the affiliating countries of authors and Loet Leydesdorff tops the list among the prolific authors. It is observed that Lotka’s Classical Law also fits the HCA data set in LIS. “Research impact measurement and research collaboration,” “Social networking” and “Research metrics and citation-based studies” are found to be the emerging areas of LIS research.,Researchers may find a way what gets cited in specific areas of LIS literature and why along with who are the prolific authors.,This study is important from the perspective of the growing research field of the LIS discipline to identify the papers that have influenced others papers as per citation count, spot the active and more impactful topics in LIS research.

中文翻译：

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作者趋势和内容分析

本文的目的是检验顶级图书馆和信息科学（LIS）期刊的高引用文章（HCA）的经典特征，并熟悉LIS特定领域的高质量著作，以区分被引用和引用的内容。下载了多篇LIS期刊上发表的HCA，对其进行了编码，并开发了具有基本元数据元素的数据库，供使用文献计量指标进行分析。洛特卡的科学生产率平方反比定律被用于评估作者的HCA生产率。内容分析方法还被用于发现寻求高被引的新兴研究领域。针对与个人生产力有关的五个研究问题，提出了推论。国家和机构生产力的协作模式，影响力较大的研究领域。荷兰是作家所有隶属国中的潜在参与者，Loet Leydesdorff在多产的作家中名列前茅。可以看出，洛特卡的《古典法》也符合LIS中的HCA数据集。LIS研究的新兴领域是“研究影响评估和研究协作”，“社交网络”以及“研究指标和基于引文的研究”。研究人员可能会找到在LIS文献和特定领域中被引用的方法。为什么？以及谁是多产的作者。，此研究从LIS学科的不断发展的研究领域的角度来看很重要，以便根据引用次数来识别影响其他论文的论文，