多维属性融合的社交媒体高影响力人物画像研究

摘要： ［目的/意义］社交媒体高影响力用户集独特的内容能力、魅力的人格化特征、自带话题的势能价值及高效的流量变现能力于一体。构建高影响力人物画像，直观展示群体人员典型特征，对扩大优秀网络文化的辐射力和感染力及平台提供精准服务、维系核心用户、监管引导舆情等具有重要作用。［研究设计/方法］依据超级IP理论，从人格、内容、流量、信任机制四方面解析高影响力用户，围绕用户基本属性、行为属性、价值属性提取标签体系构建人物画像概念模型。以微博平台高影响力用户数据为样本，运用Kmeans聚类算法实现用户所属群体划分。［结论/发现］ 实验结果表明新浪微博平台高影响力用户主要分为3类，以聚类中心点为典型代表，得到不同高影响力用户的典型人物画像，依据关键群体特征属性，提出相应的平台舆情监管、个性化服务、社交营销策略。［创新/价值］将超级IP理论与社交媒体高影响力用户特征契合，构建社交媒体高影响人物画像，为网络舆情监管引导、社交媒体平台运营发展提供新的方法与视角。

关键词: 社交媒体, 高影响力用户, 用户画像, 超级IP, K-means聚类算法

Abstract: ［Purpose/Significance］High-impact users of social media hold the features of unique content capabilities, charismatic personality, potential energy values and efficient network traffic monetizing capabilities. It is crucial to construct highimpact user profile and visualize the typical characteristics of group members so as to expand the radiation of excellent online culture and provide accurate services for platforms, maintain core users, as well as supervise and guide public opinion. ［Design/Methodology］According to the Super IP theory, the high-impact users were analyzed from four aspects, including personality, content, online traffic and trust mechanism. The label system was built upon users’ fundamental attributes, behavior attributes and value attributes in order to construct a conceptual model for the user profile. Taking high-impact users’ data from the platform of Weibo as a sample, K-means clustering algorithm was used to conduct user classification. ［Findings/Conclusion］The experimental results show that the highimpact users of Weibo can be segmented into three groups. The typical portraits of different high-impact users have been obtained based on the prototypical representatives of cluster centers. According to the characteristics of key groups, public opinion supervision, individualized services and social marketing strategies are proposed for the corresponding platforms. ［Originality/Value］The Super IP theory is combined with high-impact users’ characteristics of social media to build portraits for high-impact users, as well as provide new methods and perspectives for the online public opinion supervision and social media platform operation and development.

Keywords: Social media, High-impact user, User profile, Super IP, K-means clustering algorithm

网址：多维属性融合的社交媒体高影响力人物画像研究 https://mxgxt.com/news/view/1516142

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