Abstract: 【Purpose/significance】Continuously deepening the reform of data factor market allocation is a key aspect of the construc⁃ tion of digital China. Quantitative evaluation of data factor market policies can not only provide a reference basis for the formulation, adjustment, optimization, and improvement of related policies, but also offer research support for the ongoing effort to deepen the re⁃ form of market allocation of data factors.【Method/process】The LDA model was used to conduct content mining on 468 provincial data factor market policy texts from 2019 to 2024. The provincial data factor market policy evaluation system was constructed by combining existing literature, and 10 policy samples were quantitatively evaluated based on the PMC index model.【Result/conclusion】The study revealed that among the 10 policies, 2 were rated as excellent, 2 as passing, and the remaining 6 as good. The overall posture of China's provincial data factor market policies is positive, but there is still room for improvement. Based on this, the paper proposes five optimization suggestions aimed at improving the top-level design, enhancing policy timeliness, expanding the policy subject, grasping the policy theme, and completing the policy guarantee.【Innovation/limitation】This paper pioneers the construction of a provincial data factor market policy evaluation index system and conducts quantitative evaluations of policies based on the PMC index model. However, future studies need to delve deeper into the effects of policy implementation.