{"title":"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","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":"{\"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}","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}
Usage, captures, mentions, social media and citations of LIS highly cited papers: an altmetrics study
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.
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