【摘要】 目的：探测国际图书情报学领域的研究前沿，为国内图书情报学研究及其发展提供借鉴。方法：根据Altmetrics指标和被引频次筛选图书情报学领域的高影响力文献，引入自组织特征映射神经网络（SOFM）进行文献聚类以识别图书情报学前沿主题。结果：5个影响力较大的图书情报学前沿主题是Altmetrics指标及应用、学术评价的拓展、政府开放数据、大数据分析与应用、性别差异。结论：在引文网络的基础上采用SOFM进行文献聚类可较好地识别图书情报学前沿主题，对国际图书情报学研究前沿主题的内容分析可为国内图书情报学学者提供有益的参考。更多还原

【Abstract】 Objective To provide the reference for studies on and development of library and information science in our country by studying the frontiers in foreign studies on library and information science. Methods The high-impact papers on library and information science in foreign countries were selected according to the Altmetrics indexes and citation frequencies, and their frontier topics were identified by introducing the self-organizing feature mapping(SOFM) neural network for literature clustering. Results The 5 frontier topics in papers on library and information science with a higher impact power were Altmetric indexes and their application, expansion of academic evaluation, government open data, analysis and application of big data, and sex difference. Conclusion The SOFM neural network for literature clustering on the basis of citation network can effectively identify the frontier topics in studies on library and information science in foreign countries, and analysis of contents in frontier topics in papers on library and information science can provide useful reference for domestic scholars.更多还原