：学术期刊数据库的建设为科研论文标注基金的深入研究提供了条件。文章以国家社科基金项目为例，从CNKI数据库获取了基金项目的论文成果，对这些论文的基金标注情况进行了统计分析。采用Word2vec模型计算了论文与标注基金研究内容的相关性，并结合人工，识别出基金不实标注的现象。结果表明，论文一文多注的情况较为常见；在基金不实标注的数据中，重大项目和重点项目作为高学术影响力的项目被不实标注的比例较高。

The construction of the academic journal database provides possibility for in-depth research on the labeling of fund projects in scientific papers. In this research, the National Social Science Fund projects and the papers which labeled these fund projects were obtained from the CNKI database, and a statistical analysis was carried out on the fund labeling of these papers. Word2vec model was used to calculate the similarity of the research content between the paper and its labeled funds. Two human annotate teams were organized to make further identification of the false labeling of funds. The results show that it is common for papers to label multiple funds. Among the false labeling examples, the proportion of major projects and key projects are considerably higher.