Employment information cocoon and anxiety amplification under algorithmic recommendatio - Ying, Wang; Khalid, Nurul Fazzuan (Journal of Islamic, Social, Economics and Development, 2026)
In the social media ecosystem dominated by algorithmic recommendation technology, users are prone to form information cocoons due to long - term exposure to homogeneous employment content, which may exacerbate the occupational anxiety of the college student group. Existing research mainly focuses on the behavioral impacts of information cocoons, lacking quantitative analysis of their psychological effects and the underlying mechanisms of algorithmic technology. This study aims to reveal how the algorithmic recommendation mechanism affects occupational anxiety by constructing an employment information cocoon and to verify the moderating effect of individual cognitive reflection ability, providing theoretical support for the precise intervention of occupational anxiety in the digital age. This study adopts a quantitative research method. Through stratified sampling, 420 undergraduate students from three universities in Guangzhou, Guangdong Province, were selected as the sample. The Career Anxiety Scale and multi - level linear regression model were used for data analysis, and the Bootstrap method (with 1000 repeated samplings) was introduced to test the mediating effect. The study found that the intensity of the information cocoon has a significant positive impact on occupational anxiety (Cohen ’ s d = 2.13, p < 0.001). For every 30 - day exposure in the information cocoon, the anxiety level increases by 0.23 standard deviations. The homogenization of recommended content affects occupational anxiety through two paths: directly enhancing the perception of occupational competition (B = 0.35) and indirectly reducing occupational self - efficacy (B = 0. 19), with the total mediating effect accounting for 58.7%. Cognitive reflection ability plays a moderating role. High cognitive reflection ability can reduce the growth rate of anxiety (β = - 0.17, p = 0.032), while those with low cognitive reflection ability are prone to fall into a negative cycle. The study confirms that the algorithm - driven information cocoon is a technical inducement for occupational anxiety. Based on this, it is recommended to formulate intervention strategies from two aspects: optimizing the recommendation logic and enhancing individual cognitive reflection ability, providing an empirical basis for constructing an algorithm governance framework and a college student occupational mental health service system.