BACKGROUND: Suicidal ideation is prevalent in major depressive disorder (MDD) and is closely related to empathy and alexithymia. While traditional approaches (e.g., regression models) focus on linear associations, network analysis provides unique advantages by mapping dynamic symptom interactions and identifying pivotal nodes that may drive suicidal risk. This study investigates these relationships through a network lens to reveal actionable intervention targets. METHODS: The study included 329 adolescents with MDD (ages 12-18). The Alexithymia Scale (TAS-20), Interpersonal Reactivity Index (IRI), and the Positive and Negative Suicide Ideation scale (PNSI) were used to assess alexithymia, empathy, and suicidal ideation levels, respectively. Network analysis was conducted to model the relationships between symptoms and calculate centrality and stability indices. RESULTS: Network analysis revealed strong stability with Emotional Identification Difficulty (DIF) and Personal Distress (PD) identified as the most influential core symptoms, exhibiting the strongest bridging roles between emotional dysfunction and suicidal ideation. DIF showed particularly robust connections to both PD and suicidal ideation, while comparative subgroup analyses indicated no significant differences in network patterns between first-episode and recurrent MDD patients, suggesting consistent symptom dynamics across illness stages. CONCLUSION: By revealing DIF and PD as central therapeutic targets, this study demonstrates how network analysis can uncover intervention opportunities missed by traditional approaches. Clinically, targeting these nodes through emotion recognition training and distress tolerance interventions may disrupt the pathway to suicidality in adolescents with MDD.