How Recommendation Algorithms Drive Beauty Product Consumption: An Analysis Based on Data of University Students on TikTok

With the widespread use of social media platforms among college students, recommendation algorithms have gradually become an important mechanism influencing their consumption behavior. This paper takes the TikTok platform as the research scenario to explore the impact of recommendation algorithms on college students’ willingness to purchase beauty products. The study employs quantitative research methods, collecting 97 valid samples from a questionnaire survey. The survey content covers aspects such as usage behavior, recommendation perception, purchase history, and influencing factors. The data results are presented through methods such as proportion analysis and descriptive statistical analysis. The study found that respondents generally recognized the relevance and professionalism of TikTok's recommended content. Among them, 73.19% believed that the recommended content matched their own interests, and about 70% of respondents would make a purchase decision within 30 minutes of seeing the recommended content, showing that algorithm recommendations play a significant role in stimulating instant purchases and emotional consumption. Overall, recommendation algorithms significantly improve the purchase intention of beauty products through precise exposure and emotion enhancement mechanisms, providing a reference for social e-commerce platforms to optimize algorithm design and promote rational consumption.