Lead users are the group of most valuable users in product innovation and new product development for a certain firm. Based on web mining methods on user innovation communities, this paper presents quantitative methodology to evaluate the contributions and values of online community users to identify lead users. Firstly, we analyze user behaviors and calculate the user interest index (UII) of posts, keywords and innovation fields to measure the popularity of innovations based on other users' focus. Secondly, the model of User Innovation Knowledge supernetwork (UIKSN) is proposed, in which UIIs and user contributions are considered as two types of node weights for integrating behavior data and content data. And then, rules and methods are suggested based on the UIKSN model for identifying lead users to meet various requirements including contributions and UIIs in posts, keywords, hot frontiers, core innovation fields, and even in certain fields or knowledge points. Furthermore, knowledge structures are analyzed through ego-network analysis. Case studies show that the proposed UIKSN model and methodology are more objective and credible and thus have good potentials for identifying and analyzing lead users from multiple levels, such as posts, keywords, hot front, core innovation fields, etc.

领先用户是某家公司在产品创新和新产品开发方面最有价值的用户。基于对用户创新社区的网络挖掘方法，本文提出了定量方法，以评估在线社区用户的贡献和价值，从而确定主要用户。首先，我们分析用户行为并计算帖子，关键字和创新领域的用户兴趣指数（UII），以基于其他用户的关注度来衡量创新的受欢迎程度。其次，提出了用户创新知识超级网络（UIKSN）模型，其中UII和用户贡献被认为是用于集成行为数据和内容数据的两种节点权重。然后，建议使用基于UIKSN模型的规则和方法，以识别主要用户以满足各种要求，包括帖子，关键字，热点地区，核心创新领域甚至某些领域或知识点中的贡献和UII。此外，通过自我网络分析来分析知识结构。案例研究表明，所提出的UIKSN模型和方法更加客观，可信，因此具有从多个级别（例如，帖子，关键字，热点，核心创新领域等）识别和分析潜在用户的良好潜力。