The rise of scientific literature on Twitter research: a bibliometric analysis and some insights

IF 2.1 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE Global Knowledge Memory and Communication Pub Date : 2023-07-25 DOI:10.1108/gkmc-03-2023-0083
Aasif Ahmad Mir, Sevukan Rathinam
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Abstract

Purpose The study aims to access, monitor and visualize the scientific progress of Twitter-based research through a bibliometric analysis of scientific publications. Design/methodology/approach The data was retrieved from 2006 to February 23, 2022 using the Web of Science, a leading indexing and abstracting database. In response to the authors’ query, 6,193 items with 101,037 citations, an average citation of 16.31 and an h index of 126 were received. The “Biblioshiny” extension of the “Bibliometrics” package (www.bibliometrix.org) of R software was used to evaluate and visualize the data. Findings The present study highlighted the scientific progress of the field evolved over a period of time. The obtained results uncovered the publication trends, productive countries and their collaboration pattern, active authors who nurture the field by making their contribution, prolific source titles adopted by authors to publish the literature on the topic, most productive language in which literature was written, productive institutions, funding agencies that sponsor the research, influential articles, prominent keywords used in publications were also identified which will aid scientists in identifying research gaps in a particular area. Originality/value This study comprehensively illustrates the research status of Twitter-related research by conducting a bibliometric analysis. The study’s findings can assist relevant researchers in understanding the research trend, seeking scientific collaborators and funding for their research. Further, the study will act as a ready reference tool for the scientific community to identify research gaps, select research topics and appropriate platforms for submitting their scholarly endeavors.
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推特研究中科学文献的兴起:文献计量分析和一些见解
本研究旨在通过对科学出版物的文献计量分析,获取、监测和可视化基于twitter的研究的科学进展。设计/方法/方法数据检索时间为2006年至2022年2月23日,检索时间为Web of Science,这是一个领先的索引和摘要数据库。共收到论文6193篇,被引101037次,平均被引16.31次,h指数126。使用R软件的“Bibliometrics”软件包(www.bibliometrix.org)的“Biblioshiny”扩展对数据进行评估和可视化。本研究强调了该领域的科学进展是经过一段时间演变而来的。获得的结果揭示了出版趋势、生产国家及其合作模式、通过贡献来培育该领域的活跃作者、作者发表该主题文献时采用的多产源标题、撰写文献的最有效语言、生产机构、赞助研究的资助机构、有影响力的文章、还确定了出版物中使用的突出关键词,这将有助于科学家确定特定领域的研究差距。原创性/价值本研究通过文献计量分析全面阐述了twitter相关研究的研究现状。该研究的发现可以帮助相关研究人员了解研究趋势,寻找科学合作者和资助他们的研究。此外,该研究将作为科学界确定研究差距、选择研究主题和提交学术成果的适当平台的现成参考工具。
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来源期刊
Global Knowledge Memory and Communication
Global Knowledge Memory and Communication INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
4.20
自引率
16.70%
发文量
77
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