The impact of social media usage on algorithmic literacy among Chinese adults

In an era where algorithms dominate digital platforms, algorithmic literacy has become essential for understanding platform features, reducing informational biases, and empowering informed user decisions. This research investigates how social media use influences algorithmic literacy among Chinese adults (18–45). Using an online convenience sample (n = 951), we find that higher education and frequent social media use predict greater algorithmic awareness, which in turn fosters behaviors to counteract algorithmic filtering; age shows no effect. Awareness reduces ambivalence, strengthens positive attitudes, and weakens negative ones – particularly towards prioritizing algorithms. These effects are moderated by accuracy motivation and locus of control (LOC): both amplify awareness’s impact by increasing positivity and reducing negativity. Users with higher perceived control exhibit more favorable, less ambivalent attitudes. Though interaction terms modestly improved model fit, motivation and LOC independently outperformed awareness in explaining attitudes. Education and social media use also directly influence evaluations. Models best explained positive attitudes, but poorly predicted ambivalent or negative ones. In comparison to their U.S. and German counterparts, Chinese users report higher engagement but varied awareness. This study shows that motivation and perceived control, beyond awareness, are key to shaping algorithm-related attitudes – underscoring the need for targeted algorithmic literacy in non-Western contexts.