[Purpose/significance] Algorithm recommendation APP has attracted a large number of users, and improv⁃ ing user retention has been the focus of all kinds of APP. This study explores the influencing factors of user churn be⁃ havior, and provides suggestions and countermeasures to reduce user churn and improve user experience. [Method/ process] The paper obtained 9772 comments from the users of the algorithm recommendation APP. The grounded theo⁃ ry was applied to code the data to clarify the influencing factors of user churn behavior and build the influencing factors model of user churn behavior of the algorithm recommendation APP. [Result/conclusion] Information factors, environ⁃ mental factors, system factors, and online communities influence user churn behavior by affecting users’sense of con⁃ trol, and users’information literacy plays a moderating role in the sense of control and user churn behavior.