摘要：

目的 构建一种基于增强型引文数据的期刊代表作评价方法，为评估期刊代表作在学术共同体中的认可情况提供新思路。 方法 阐述增强型引文数据的建构逻辑，提出以学术共同体评议信息为核心依据的期刊代表作评价方法，以信息资源管理学科高水平期刊样本论文为分析对象，通过典型案例深入考察期刊代表作在学术共同体中的影响范围与认可情况，验证本研究所提评价方法的有效性。 结果 基于增强型引文数据，可以看出分析对象在学科、期刊、机构、学者等方面获得了学术共同体的广泛认可，提出的专业术语引领了特定领域的发展。 结论 该方法可以充分发挥增强型引文数据的语义纽带作用，实现复杂维度下的多维映射与关联分析，为考察学术期刊的学术引领力与知识认证成效提供有力工具。

关键词: 增强型引文数据, 期刊代表作, 期刊评价, 期刊诊断性评价, 知识认证, 知识地标

Abstract:

Purposes To develop a method for evaluating journal representative works based on augmented citation data， thereby providing a new approach to assessing the recognition of such articles within the academic community. Methods This study elucidates the construction logic of augmented citation data， proposes a method for evaluating journal representative works based primarily on peer review information from the academic community. Taking papers published in high-impact journals in the field of Information Resource Management as the analysis subjects， the study uses typical case studies to thoroughly examine the scope of the influence and recognition of journal representative articles within the academic community， thereby validating the effectiveness of the evaluation method. Findings Based on the augmented citation data， it is evident that the subject of analysis has gained relatively broad recognition within the academic community across disciplines， journals， institutions， and scholars， and that the specialized terminology it has introduced has driven the development of specific fields. Conclusions This method fully harnesses the semantic linkages inherent in augmented citation data to enable multidimensional mapping and association analysis across complex dimensions， thereby providing a powerful tool for assessing the academic leadership and knowledge validation effectiveness of academic journals.

Key words: Augmented citation data, Journal representative works, Journal evaluation, Diagnostic evaluation of journal, Knowledge certification, Knowledge landmark