The Research On User Acceptance Behavior Of Algorithm Recommendation Information

In the era of mobile Internet with redundant information,the Application of recommendation algorithm has changed the mode of information distribution and reshaped the way users obtain and receive information.Based on this,it is very vital to discuss users’ perception and acceptance of algorithm recommendation information.Based on the Application scenarios of Algorithmic recommendation Apps on Chinese mobile terminals,the research perspective is from the demand side of the audience,aiming to draw a cognitive picture of Chinese Internet users’ acceptance behavior of algorithmic recommendation information by exploring the acceptance behavior path of mobile platform users on personalized algorithm recommendation information and the internal relationship of influencing factors.Understand users’ sense of experience and acceptance of algorithmic recommendation Apps and personalized recommendation information,and provide constructive suggestions to relevant stakeholders involved in algorithmic recommendation platforms.Based on the theory of planned behavior(TPB),a model of user acceptance behavior for algorithmic recommendation information was developed.By using literature analysis method,in-depth interview method,questionnaire survey method and statistical analysis method,529 questionnaire data were used to empirically study users’ intention and behavior path to accept algorithmic recommendation information.The results show that the user’s skill,acceptance attitude and subjective norm positively affect the acceptance intention of algorithm recommendation information.Perceptual behavior control positively influences the acceptance intention and acceptance behavior of algorithm recommendation information.Acceptance intention plays a mediating role between perceptual behavior control and acceptance behavior of algorithm recommendation information.Algorithm perception and online privacy literacy have no significant influence on the acceptance intention of algorithm recommendation information.In order to standardize the algorithm recommendation and its users’ acceptance behavior,regulators should regulate and standardize the algorithm recommendation service with systemically dynamic laws and regulations.Platform side should grasp the underlying logic of algorithm recommendation information service to improve user experience;Users should enhance their self-consciousness to critically accept the recommended information of the algorithm,such as paying attention to the cultivation of personal Internet use skills,enhancing and improving personal privacy concerns and privacy control ability,striving for autonomous control of the decision-making power of the algorithm,and critically embracing the algorithm culture.