【摘要】 【目的/意义】在线健康社区核心用户识别，对社区可持续发展与社会科学的健康信息传播具有重要意义。【方法/过程】本文提出的核心用户识别方法综合考虑了用户属性特征和社会网络特征。首先利用Node2vec网络表示学习模型将用户关注网络中的节点映射为向量，并选择最优的聚类算法对用户节点向量进行聚类及筛选，最后引入市场营销领域客户价值细分模型（RFM模型），构建融合社会网络特征的核心用户影响力评价模型，对核心用户候选集综合分析后得到在线健康社区核心用户排名。【结果/结论】选取丁香园论坛中的数据对本文所提方法进行验证，证明了本文所提方法的有效性，结果表明该方法可以较好地识别在线健康社区的核心用户。【创新/局限】引入RFM模型考虑时间、频率和价值因素等多维关键指标的影响，从用户价值角度能够较好地表征和识别核心用户，但未充分考虑核心用户影响力的动态演化过程，未来可考虑结合时间维度进一步探索核心用户识别的动态机制。更多还原

【Abstract】 【Purpose/significance】The core users identification of online health community is important for the sustainable development of the community and the dissemination of scientific health information in the society.【Method/process】The core users identification method proposed in this paper integrates user attribute features and social network features. Firstly, we use the Node2vec network representation learning model to map the nodes in the user’s social network as vectors, and select the optimal clustering algorithm to cluster and filter the user node vectors, and finally introduce the customer value segmentation model(RFM model) in the field of marketing to construct the core user influence evaluation model integrating the social network characteristics, and then we obtain the core user ranking of the online health community after the comprehensive analysis of the candidate set.【Result/conclusion】We selected the data in DingXiangYuan Forum to validate the method proposed in this paper, and proved the effectiveness of the method proposed in this paper, and the results show that the method can better identify the core users of online health community.【Innovation/limitation】We introduced the RFM model to consider the influence of multi-dimensional key indicators such as time, frequency and value factors, which can better characterize and identify core users from the perspective of user value, but does not adequately consider the dynamic evolution process of the influence of core users, so we can consider combining with the time dimension to further explore the dynamic mechanism of core user identification in the future.更多还原