{"title":"基于文献计量学的全球社交机器人研究趋势可视化分析","authors":"Xiujuan Chen, Shanbing Gao, Xue Zhang","doi":"10.1108/oir-06-2021-0336/v2/decision1","DOIUrl":null,"url":null,"abstract":"PurposeIn order to further advance the research of social bots, based on the latest research trends and in line with international research frontiers, it is necessary to understand the global research situation in social bots.Design/methodology/approachChoosing Web of Science™ Core Collections as the data sources for searching social bots research literature, this paper visually analyzes the processed items and explores the overall research progress and trends of social bots from multiple perspectives of the characteristics of publication output, major academic communities and active research topics of social bots by the method of bibliometrics.FindingsThe findings offer insights into research trends pertaining to social bots and some of the gaps are also identified. 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引用次数: 2
摘要
为了进一步推进社交机器人的研究,有必要根据最新的研究趋势,并与国际研究前沿接轨,了解全球社交机器人的研究现状。设计/方法/途径选择Web of Science™核心馆藏作为搜索社交机器人研究文献的数据源,采用文献计量学的方法,从出版物产出特征、主要学术群体和社交机器人活跃研究课题等多个角度,对所处理的项目进行可视化分析,探讨社交机器人的整体研究进展和趋势。这些发现为有关社交机器人的研究趋势提供了见解,也发现了一些差距。建议今后进一步扩大社交机器人的研究对象,不要只关注Twitter平台,加强对社交机器人实时检测方法的研究和对社交机器人法律伦理问题的讨论。大多数现有的评论都是针对社交机器人的检测方法和技术。与上述综述不同的是,本研究是一种系统的文献综述,通过定量分析的方法,全面梳理了社交机器人领域的研究成果,展示了该领域最新的研究趋势,并提出了一些未来需要重点关注的研究方向。研究结果将为后续学者对社交机器人的研究提供参考。同行评议本文的同行评议历史可在:https://publons.com/publon/10.1108/OIR-06-2021-0336。
Visual analysis of global research trends in social bots based on bibliometrics
PurposeIn order to further advance the research of social bots, based on the latest research trends and in line with international research frontiers, it is necessary to understand the global research situation in social bots.Design/methodology/approachChoosing Web of Science™ Core Collections as the data sources for searching social bots research literature, this paper visually analyzes the processed items and explores the overall research progress and trends of social bots from multiple perspectives of the characteristics of publication output, major academic communities and active research topics of social bots by the method of bibliometrics.FindingsThe findings offer insights into research trends pertaining to social bots and some of the gaps are also identified. It is recommended to further expand the research objects of social bots in the future, not only focus on Twitter platform and strengthen the research of social bot real-time detection methods and the discussion of the legal and ethical issues of social bots.Originality/valueMost of the existing reviews are all for the detection methods and techniques of social bots. Unlike the above reviews, this study is a systematic literature review, through the method of quantitative analysis, comprehensively sort out the research output in social bots and shows the latest research trends in this area and suggests some research indirections that need to be focused in the future. The findings will provide references for subsequent scholars to research on social bots.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2021-0336.