The Positive and Negative Impacts of Social Media Algorithms on Consumer Behavior and Optimization Strategies

The effects of social media algorithms on consumer behavior have received considerable attention, but the strategies to assuage the negative effects of it remain insufficient. This paper analyzes the dual influences of algorithmic mechanisms, which is on the one hand, enhance efficiency meanwhile inducing information cocoons and polarization and on the other hand, cause the influence on psychological and behavioral outcomes. The study reveals that while algorithms improve information matching and reduce decision costs, the system, in the meantime, concurrently diminishes content diversity and increases political polarization rates, alongside pervasive privacy risks. To address these issues, this paper proposes: First, developing explainable recommendation systems as well as real-time user fatigue monitoring to enhance transparency and responsiveness. Second, cultivating algorithmic literacy education as well as active information-seeking behavior for the empowerment of users. These recommendations seek to strike a balance between personalized services and responsible design for the promotion of an equitable digital ecosystem.