Digital twin networks (DTNs) rely on mobile users to mitigate sensing and computing burdens of digital twin service platforms (DTSPs), but suffer from limited user resources, and dual information asymmetry. To address these issues, we propose a contract incentive mechanism for digital twin data sensing and computing under dual information asymmetry. Specifically, we map the DTN to a labor market, fully accounting for mobile users’ selfish tendencies and the dual asymmetry of information. We construct a three-dimensional contract model encompassing three core components: sensed data volume, basic salary, and performance coefficient, which comprehensively aligns with the interests of both DTSP and users. By incorporating individual rationality (IR) and incentive compatibility (IC) constraints, we formulate a rigorous optimization problem aimed at maximizing the DTSP’s utility. Simulation results verify the effectiveness of the contract incentive mechanism in revealing private types and maximizing DTSP utility.