BACKGROUND: Each year, there are approximately 10.3 million new stroke cases worldwide, with 2 million occurring in China. Post-stroke depression (PSD) is a common complication that negatively affects rehabilitation outcomes and increases long-term mortality. OBJECTIVE: This study used network analysis to investigate the cross-sectional and longitudinal networks between depressive symptoms in new-onset stroke patients with PSD, aiming to identify the key symptoms and predictive relationships among distinct symptoms during the acute phase and 6 months after the stroke. METHODS: This longitudinal descriptive study collected data from October 2022 to December 2023, including eligible new-onset stroke patients. Depressive symptoms were assessed using the CES-D scale, and network analysis was used to analyze the interactions between symptoms. RESULTS: 613 participants completed the data collection. The study found that D3 (Felt sadness) emerged as the central depressive symptom at both baseline and follow-up (EI value = 1.215 and 1.168, respectively). In the longitudinal network analysis, D7 (Sleep quality) displayed the strongest out-Expected Influence (value = 1.728), while D4 (Everything was an effort) showed the strongest in-Expected Influence (value = 1.322). LIMITATIONS: The self-report measure is adopted for all depressive symptoms in the study, and there may be some deviation. CONCLUSION: These symptom-level associations at cross-sectional and longitudinal networks extend our understanding of PSD symptoms in new-onset stroke patients by pointing to specific key depressive symptoms that may aggravate PSD. Recognizing these symptoms is imperative for the development of targeted interventions and treatments aimed at addressing PSD in new-onset stroke patients.