Mining product adoption intentions from social media could provide insights for many business practices, such as social media marketing. Existing methods mainly focus on text information but overlook other types of data. In light of the Integrated Behavioral Model (IBM), in this study, we argue that it is valuable to consider users’ social connections in addition to postings for identifying product adoption intentions. Based on this rationale, we propose a novel multiview deep learning framework to identify product adoption intentions. Extensive experiments show our proposed approach is effective, and demonstrate the benefit of incorporating social network information for intention identification.

从社交媒体挖掘产品采用意图可以为许多商业实践提供见解，例如社交媒体营销。现有方法主要关注文本信息，而忽略了其他类型的数据。根据集成行为模型 (IBM)，在本研究中，我们认为，除了用于识别产品采用意图的帖子外，考虑用户的社交关系也很有价值。基于这一基本原理，我们提出了一种新颖的多视图深度学习框架来识别产品采用意图。大量实验表明，我们提出的方法是有效的，并证明了结合社交网络信息进行意图识别的好处。