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
{"title":"Usage, captures, mentions, social media and citations of LIS highly cited papers: an altmetrics study","authors":"M. Saberi, Faezeh Ekhtiyari","doi":"10.1108/PMM-10-2018-0025","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe 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).\n\n\nDesign/methodology/approach\nThis 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.\n\n\nFindings\nThe 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.\n\n\nOriginality/value\nAltmetrics 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.\n","PeriodicalId":44583,"journal":{"name":"Performance Measurement and Metrics","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2019-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/PMM-10-2018-0025","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Performance Measurement and Metrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/PMM-10-2018-0025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
Performance Measurement and Metrics
Performance Measurement and Metrics INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
2.20
自引率
0.00%
发文量
1
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
期刊最新文献
First-gen and the library: a survey of student perceptions of academic library services Predicting student success with and without library instruction using supervised machine learning methods What space are you looking for? An evaluation of organizational climate and its relationship with job burnout in hospital and college libraries Revise, redUX, re-cycle: iterative website usability studies in an assessment cycle
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1