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A bibliometric analysis of topic modelling studies (2000-2017)

机译:主题建模研究的伯格计分析(2000-2017)

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摘要

Topic modelling is a powerful text mining tool that has been applied in many fields such as software engineering, political and linguistic sciences. To evaluate the development of topic modelling studies, the present study reports a bibliometric analysis of SCIE, SSCI and A&HCI listed articles published from 2000 and 2017. Bibliometric indices for productive authors, countries and institutions are analysed. In addition, thematic changes concerning topic modelling are also examined. Results show that China plays a leading role in this field. Topic modelling has established itself as an important technique in not only natural and formal sciences but also social sciences. LDA, social networks and text analysis are the topics with increasing popularity, while certain models (e.g. pLSA) and applications (e.g. topic detection) are declining in popularity. The findings could help researchers optimise research topic choices, seek collaboration with appropriate partners and stay up-to-date with the development of the field.
机译:主题建模是一种强大的文本挖掘工具,已应用于许多领域,如软件工程,政治和语言科学。为了评估主题建模研究的发展,本研究报告了从2000年和2017年发布的SCIE,SSCI和A&HCI列出的文章的生物毛测量计分析。分析了生产作者,国家和机构的生学计量指标。此外,还检查了关于主题建模的主题变更。结果表明,中国在这一领域发挥着主导作用。主题建模在不仅是自然和正规的科学,而且是社会科学的重要技术。 LDA,社交网络和文本分析是具有越来越普及的主题,而某些模型(例如PLSA)和应用(例如,主题检测)在普及的下降。调查结果可以帮助研究人员优化研究主题选择,寻求与适当的合作伙伴的合作,并与现场的发展保持最新。

著录项

  • 来源
    《Journal of Information Science》 |2021年第2期|161-175|共15页
  • 作者

    Xin Li; Lei Lei;

  • 作者单位

    School of Foreign Languages Huazhong University of Science and Technology China;

    School of Foreign Languages Huazhong University of Science and Technology China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Bibliometric analysis; topic modelling; Web of Science;

    机译:Bibliometric分析;主题建模;科学网;
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