In online discussion forums, users are more motivated to take part in discussions when observing other users’ participation—the effect of social influence among forum users. In this paper, we study how to utilize social influence for increasing the overall forum participation. To this end, we propose a mechanism to maximize user influence and boost participation by displaying forum threads to users. We formally define the participation maximization problem, and show that it is a special instance of the social welfare maximization problem with submodular utility functions and it is NP-hard. However, generic approximation algorithms is impracticable for real-world forums due to time complexity. Thus we design a heuristic algorithm, named Thread Allocation Based on Influence (TABI), to tackle the problem. Through extensive experiments using a dataset from a real-world online forum, we demonstrate that TABI consistently outperforms all other algorithms in maximizing participation. The results of this work demonstrates that current recommender systems can be made more effective by considering future influence propagations. The problem of participation maximization based on influence also opens a new direction in the study of social influence.