阿拉伯引文索引:更好地理解阿拉伯科学文献

IF 4.1 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Quantitative Science Studies Pub Date : 2023-09-15 DOI:10.1162/qss_a_00261
Jamal El-Ouahi
{"title":"阿拉伯引文索引:更好地理解阿拉伯科学文献","authors":"Jamal El-Ouahi","doi":"10.1162/qss_a_00261","DOIUrl":null,"url":null,"abstract":"Abstract The Arabic Citation Index (ARCI) was launched in 2020. This article provides an overview of the scientific literature contained in this new database and explores its possible usage in research evaluation. As of May 2022, ARCI had indexed 138,283 scientific publications published between 2015 and 2020. ARCI’s coverage is characterized by using the metadata available in scientific publications. First, I investigate the distributions of the indexed literature at various levels (research domains, countries, languages, open access). Articles make up nearly all the documents indexed with a share of 99% of ARCI. The Arts & Humanities and Social Sciences fields have the highest concentration of publications. Most indexed journals are published in Egypt, Algeria, Iraq, Jordan, and Saudi Arabia. About 8% of publications in ARCI are published in languages other than Arabic. Second, I use an unsupervised machine learning model, Latent Dirichlet Allocation, and the text mining algorithm of VOSviewer to uncover the main topics in ARCI. These methods provide a better understanding of ARCI’s thematic structure. Next, I discuss how ARCI can complement global standards in the context of a more inclusive research evaluation. Finally, I suggest a few research opportunities after discussing the findings of this study.","PeriodicalId":34021,"journal":{"name":"Quantitative Science Studies","volume":"75 1","pages":"0"},"PeriodicalIF":4.1000,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The Arabic Citation Index: Toward a better understanding of Arab scientific literature\",\"authors\":\"Jamal El-Ouahi\",\"doi\":\"10.1162/qss_a_00261\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The Arabic Citation Index (ARCI) was launched in 2020. This article provides an overview of the scientific literature contained in this new database and explores its possible usage in research evaluation. As of May 2022, ARCI had indexed 138,283 scientific publications published between 2015 and 2020. ARCI’s coverage is characterized by using the metadata available in scientific publications. First, I investigate the distributions of the indexed literature at various levels (research domains, countries, languages, open access). Articles make up nearly all the documents indexed with a share of 99% of ARCI. The Arts & Humanities and Social Sciences fields have the highest concentration of publications. Most indexed journals are published in Egypt, Algeria, Iraq, Jordan, and Saudi Arabia. About 8% of publications in ARCI are published in languages other than Arabic. Second, I use an unsupervised machine learning model, Latent Dirichlet Allocation, and the text mining algorithm of VOSviewer to uncover the main topics in ARCI. These methods provide a better understanding of ARCI’s thematic structure. Next, I discuss how ARCI can complement global standards in the context of a more inclusive research evaluation. Finally, I suggest a few research opportunities after discussing the findings of this study.\",\"PeriodicalId\":34021,\"journal\":{\"name\":\"Quantitative Science Studies\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2023-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quantitative Science Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1162/qss_a_00261\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Science Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1162/qss_a_00261","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 3

摘要

阿拉伯语引文索引(ARCI)于2020年启动。本文概述了这个新数据库中包含的科学文献,并探讨了其在研究评估中的可能用途。截至2022年5月,ARCI索引了2015年至2020年间发表的138283篇科学出版物。ARCI的覆盖范围的特点是使用科学出版物中可用的元数据。首先,我调查了索引文献在不同层次(研究领域、国家、语言、开放获取)的分布。文章几乎构成了所有被索引的文档,占ARCI的99%。艺术&;人文和社会科学领域的出版物最集中。大多数被索引的期刊出版于埃及、阿尔及利亚、伊拉克、约旦和沙特阿拉伯。约有8%的出版物以阿拉伯文以外的语文出版。其次,我使用无监督机器学习模型,潜狄利克雷分配和VOSviewer的文本挖掘算法来揭示ARCI中的主要主题。这些方法有助于更好地理解ARCI的主题结构。接下来,我将讨论ARCI如何在更具包容性的研究评估背景下补充全球标准。最后,在讨论了本研究的发现后,我提出了一些研究机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
The Arabic Citation Index: Toward a better understanding of Arab scientific literature
Abstract The Arabic Citation Index (ARCI) was launched in 2020. This article provides an overview of the scientific literature contained in this new database and explores its possible usage in research evaluation. As of May 2022, ARCI had indexed 138,283 scientific publications published between 2015 and 2020. ARCI’s coverage is characterized by using the metadata available in scientific publications. First, I investigate the distributions of the indexed literature at various levels (research domains, countries, languages, open access). Articles make up nearly all the documents indexed with a share of 99% of ARCI. The Arts & Humanities and Social Sciences fields have the highest concentration of publications. Most indexed journals are published in Egypt, Algeria, Iraq, Jordan, and Saudi Arabia. About 8% of publications in ARCI are published in languages other than Arabic. Second, I use an unsupervised machine learning model, Latent Dirichlet Allocation, and the text mining algorithm of VOSviewer to uncover the main topics in ARCI. These methods provide a better understanding of ARCI’s thematic structure. Next, I discuss how ARCI can complement global standards in the context of a more inclusive research evaluation. Finally, I suggest a few research opportunities after discussing the findings of this study.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Quantitative Science Studies
Quantitative Science Studies INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
12.10
自引率
12.50%
发文量
46
审稿时长
22 weeks
期刊介绍:
期刊最新文献
Technological Impact of Funded Research: A Case Study of Non-Patent References Socio-cultural factors and academic openness of world countries Scope and limitations of library metrics for the assessment of ebook usage: COUNTER R5 and link resolver The rise of responsible metrics as a professional reform movement: A collective action frames account New methodologies for the digital age? How methods (re-)organize research using social media data
×
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