学术社交网站在学术交流中的使用:范围综述

Milkyas Hailu , Jianhua Wu
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引用次数: 8

摘要

本研究对115篇关于学术社交网站在学术交流中的使用的文献进行了系统分析。以往对该主题的研究主要采取学科和用户的角度。本研究概念化了在社会互动和技术本身之间的空间中,在学术交流中使用自动神经网络。关键词分析和范围审查方法被用于分析该领域的综合文献。该研究发现,促使学者使用自动识别网络的因素存在地域差异。学者发现和分享是文献中确定的主要驱动因素。研究文献提出了四个主要主题:动机和用途、影响评估、特征和服务以及学术大数据。研究发现,近年来学术界对大数据的研究有所增加。本文还讨论了每个主题中所述的主要发现和概念。这让学者们更好地了解了人工神经网络可以做什么以及它们的弱点,并确定了值得在未来研究中解决的文献空白。我们建议未来的研究也可以扩展现有的理论框架和认识论方法,以更好地预测和澄清学术交流中使用自动神经网络的社会技术维度。此外,本研究对学术与研究机构、图书馆与资讯素养计划,以及未来的研究亦有启示。
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The Use of Academic Social Networking Sites in Scholarly Communication: Scoping Review

This research provides a systematic analysis of 115 previous literatures on the use of academic social networking sites (ASNs) in scholarly communication. Previous research on the subject has mainly taken a disciplinary and user perspective. This research conceptualizes the use of ASNs in scholarly communication in the space between social interactions and the technologies themselves. Keyword analysis and scoping review approaches have been used to analyze the comprehensive literature in the field. The study found a geographic variation in what motivates academics to use ASNs. Scholar discovery and sharing are the primary driving factors identified in the literature. Four main themes within the research literature are proposed: motivation and uses, impact assessment, features and services, and scholarly big data. The study found that there has been an increase in scholarly big data research in recent years. The paper also discusses the key findings and concepts stated in each theme. This gives academics a better understanding of what ASNs can do and their weaknesses, and identifies gaps in the literature that are worth addressing in future investigations. We suggest that future studies may also extend the existing theoretical framework and epistemological approaches to better predict and clarify the socio-technical dimensions of ASNs use in scholarly communication. In addition, this study has implications for academic and research institutions, libraries and information literacy programs, and future studies on the topic.

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来源期刊
Data and information management
Data and information management Management Information Systems, Library and Information Sciences
CiteScore
3.70
自引率
0.00%
发文量
0
审稿时长
55 days
期刊最新文献
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