【目的/意义】 学者画像被广泛运用于学术领域的各项精准服务，如论文评审、项目评审、精准推送、人才引进等。在“小同行”学者的识别中，主题标签起着关键性作用。对学者主题标签计算方法进行优化，可以更准确找到各细分学科领域的“小同行”学者。 【方法/过程】 提出一种理论框架，即学者领域画像应综合考虑学者研究兴趣与学术能力等评价信息，同时呈现学者的研究领域及其在该领域的学术水平。将主题标签与评价数据相结合，以评价数据作为主题标签权重的考量要素，提出一种计算学者高分主题标签的算法，包含发表文献量、学者署名位次、论文被引频次3个维度。 【结果/结论】 从学者本人画像来看，通过学者高分主题标签可以刻画该学者主要的细分研究领域；从学科领域找专家的需求出发，通过学者高分主题标签可找出该领域的高影响力学者。

[Purpose/Significance] Scholar profiles are widely applied in various precision services within the academic field, such as paper review, project evaluation, targeted recommendations, and talent recruitment. Topic tags play a critical role in identifying scholars in the same specialized subfield. This paper optimizes the method for calculating scholar topic tags to more accurately identify scholars within specific subdisciplines. [Method/Process] This paper proposed a theoretical framework: scholar profiles should comprehensively incorporate evaluation information such as scholars' research interests and academic capabilities, while also reflecting their research fields and academic standing within those fields. This paper integrated topic tags with evaluation data, using the latter as a factor for weighting topic tags. An algorithm was proposed for calculating high-scoring topic tags for scholars, incorporating three dimensions: the quantity of published papers, the author's position in the author list, and the citations of the papers. [Result/Conclusion] From the perspective of individual scholar profiling, high-score topic tags can delineate the main specialized research areas of a scholar. For the need to identify experts within a discipline, high-score topic tags can help pinpoint the most outstanding and core scholars in that field.