Usage, captures, mentions, social media and citations of LIS highly cited papers: an altmetrics study

IF 1.8 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

Performance Measurement and Metrics Pub Date : 2019-02-04 DOI:10.1108/PMM-10-2018-0025

M. Saberi, Faezeh Ekhtiyari

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引用次数: 27

Abstract

Purpose The purpose of this paper is to investigate the usage, captures, mentions, social media and citations of highly cited papers of Library and information science (LIS). Design/methodology/approach This study is quantitative research that was conducted using scientometrics and altmetrics indicators. The research sample consists of LIS classic papers. The papers contain highly cited papers of LIS that are introduced by Google Scholar. The research data have been gathered from Google Scholar, Scopus and Plum Analytics Categories. The data analysis has been done by Excel and SPSS applications. Findings The data indicate that among the highly cited articles of LIS, the highest score regarding the usage, captures, mentions and social media and the most abundance of citations belong to “Citation advantage of open access articles” and “Usage patterns of collaborative tagging systems.” Based on the results of Spearman statistical tests, there is a positive significant correlation between Google Scholar Citations and all studied indicators. However, only the correlation between Google Scholar Citations with capture metrics (p-value = 0.047) and citation metrics (p-value = 0.0001) was statistically significant. Originality/value Altmetrics indicators can be used as complement traditional indicators of Scientometrics to study the impact of papers. Therefore, the Altmetrics knowledge of LIS researchers and experts and practicing new studies in this field will be very important.

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LIS高引用论文的使用、捕获、提及、社交媒体和引用：一项altmetrics研究

目的本研究旨在调查图书馆与信息科学（LIS）高被引论文的使用、捕获、提及、社交媒体和引用情况。设计/方法论/方法本研究是使用科学计量学和altmetrics指标进行的定量研究。研究样本由LIS经典论文组成。这些论文包含谷歌学者介绍的LIS的高引用论文。研究数据来自谷歌学者、Scopus和Plum分析类别。数据分析采用Excel和SPSS软件进行。数据表明，在LIS的高引用文章中，使用、捕获、提及和社交媒体得分最高，引用次数最多的是“开放获取文章的引用优势”和“协作标签系统的使用模式”，谷歌学者引文与所有研究指标之间存在显著正相关。然而，只有谷歌学者引文与捕获指标（p值=0.047）和引文指标（p价值=0.0001）之间的相关性具有统计学意义。原创性/价值Altmetrics指标可以作为科学计量学传统指标的补充，研究论文的影响。因此，LIS研究人员和专家的Altmetrics知识以及在该领域进行新的研究将非常重要。

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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来源期刊

Performance Measurement and Metrics INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

2.20

自引率

0.00%

发文量

期刊介绍： ■Quantitative and qualitative analysis ■Benchmarking ■The measurement and role of information in enhancing organizational effectiveness ■Quality techniques and quality improvement ■Training and education ■Methods for performance measurement and metrics ■Standard assessment tools ■Using emerging technologies ■Setting standards or service quality