In open innovation platforms, users learn external knowledge through network interaction, and their position in the interactive network has an impact on the user’s sustainable knowledge contribution. Due to the gap in knowledge level, users’ absorption and utilization efficiency of external knowledge is not consistent. We studied the differences in user sustainable knowledge contribution behavior from the perspective of knowledge absorption. We crawled the data of a typical open innovation platform, used LDA to identify the level of user knowledge diversity and social network technology to analyze the user’s network location, and used the negative binomial regression model for empirical analysis. Our results show that knowledge diversity positively affects user knowledge contribution, and network breadth and network depth have positive and negative effects on user knowledge contribution behavior, respectively. In addition, the level of user knowledge diversity moderates the influence of network location on knowledge contribution. In summary, this research not only provides a comprehensive perspective on our current understanding of the contribution behavior of open innovation platforms, but also provides an in-depth understanding of how open innovation platforms can be properly designed to promote continuous contributions.