Concern or Fatigue? Understanding Users’ Reaction to Privacy Protection in Social Media Intelligence Recommendation

Intelligent recommendation, which recommends content by collecting and analyzing users’ personal and behavioral information, is widely used in social media to meet people’s increasing demand for personalized information. However, it has also caused users to be concerned about privacy security and even triggered fatigue about privacy protection. In order to understand users’ reactions to social media intelligent recommendations, based on Multidimensional Developmental Theory and Protection Motivation Theory, this study proposes a research model to investigate the factors influencing users’ privacy concerns and privacy fatigue. Moreover, we empirically test this model through an online survey of 229 users in the context of social media intelligence recommendations. This study come with the following findings: First, privacy settings affordance and privacy policy effectiveness positively affect the user’s self-efficacy, and privacy policy effectiveness affects the user’s response efficacy; Second, self-efficacy negatively affects users’ privacy concerns, and there is an upward U-shaped relationship between response efficacy and privacy concerns; Third, privacy concerns positively affects privacy fatigue, and fully mediates the effects of self-efficacy and response efficacy on privacy fatigue. Moreover, Theoretical and practical implications and limitations are also discussed in the end.