文章提出了一种半监督自动化用户价值识别与预测方法，完成用户群体价值建模和未知用户价值预测建模。首先提出了LRCFP特征模型，采用自组织映射神经网络SOM聚类算法对社交媒体用户建立细分模型，构建用户群体价值画像；计算并检测其CH指标值以验证LRCFP特征模型和SOM聚类模型的有效性；然后利用决策树模型预测未知用户的价值。以Bilibili社交媒体用户数据做了实例验证，说明了本文建模和方法的有效性。将用户价值分成5个等级，并分析了每个等级的用户特征。

This paper proposes a semi-supervised automatic value recognition and prediction method to accomplish user group value modeling and unknown user value prediction modeling. Firstly, the LRCFP feature model is proposed, and SOM clustering algorithm is used to subdivide the social media users; thus the user group portrait is constructed The CH index is used to verify the validity of the LRCFP feature model and the SOM clustering model. Then, the decision tree model is used to predict the unknown user value. The authors take Bilibili social media platform as an example to illustrate the validity of the proposed modeling and method. User value is divided into five grades, and user characteristics of each grade are analyzed.