There are more and more macrotasks on the crowdsourcing platforms. Macrotasks require the professional skills of the workers and the collective contributions of the teams. Social networks provide a platform for cooperation among social workers. In fact, there are few studies paying close attention to the social network between crowdsourcing workers. The problem of task assignment in crowdsourcing is NP-hard and the participants may misreport their prices in order to gain more utilities. Therefore, a Truthful Mechanism for Crowdsourcing task assignment in Social Network (TMC-SN) was proposed. The problem of crowdsourcing task assignment in social network was modeled as an auction, where the task requester is the buyer, the workers are the sellers, and the crowdsourcing platform is served as an auctioneer. In order to find the most suitable team, TMC-SN measured worker fitness to the team from both marginal contribution and team cohesion. Theoretical analysis verifies that TMC-SN has economic properties such as truthfulness, individual rationality, and budget balance. Experimental results show that TMC-SN has certain advantages in social welfare, and can improve the utilities of workers.