ObjectiveMental health problems are increasingly prevalent among college students, with depression, anxiety, and stress symptoms frequently co-occurring and mutually influencing one another. This study employed network analysis to examine the interrelationships among depression, anxiety, and stress symptoms in Chinese college students, aiming to identify potential targets to generate hypotheses for future precision-based interventions.MethodsA cross-sectional survey was conducted among college students at a Chinese university using the Depression Anxiety Stress Scale-21 (DASS-21). A Gaussian Graphical Model (GGM) combined with the graphical Least Absolute Shrinkage and Selection Operator (graphical LASSO) was used to construct the symptom network. Expected Influence (EI) was computed to identify central symptoms, and Bridge Expected Influence (Bridge EI) was calculated to identify bridge symptoms connecting different dimensions. Network structure visualization was also performed.ResultsThe symptom network revealed extensive positive connections among the 21 symptom nodes, with notable variation in edge strength. Central symptom analysis indicated that A15 (feeling of panic, EI = 2.06), S12 (difficulty relaxing, EI = 1.42), and A20 (feeling scared without reason, EI = 1.16) exhibited the highest expected influence. Bridge symptom analysis revealed that S8 (nervous tension, Bridge EI Z = 2.12), A15 (feeling of panic, Bridge EI Z = 1.70), and D13 (feeling downhearted and blue, Bridge EI Z = 1.51) were the key bridges connecting the depression, anxiety, and stress dimensions. Notably, A15 and S8 simultaneously ranked among the top central and bridge symptoms, indicating that these symptoms are identified as key nodes in both overall network activation and cross-dimensional symptom propagation.ConclusionFeeling of panic, nervous tension, and difficulty relaxing are the central symptoms of mental health problems among college students, while nervous tension and feeling of panic simultaneously serve as bridge symptoms connecting different psychological problem dimensions. These symptoms represent theoretically-motivated candidate targets for future research. The findings support the application of transdiagnostic intervention strategies in college student mental health services.