In　the　context　of　high-quality　development　and　regional　integration,　understanding　the　impact　of　spatial　correlation　network　structure　(SCNS)　of　urban　agglomerations　on　high-quality　economic　development　(HQED)　is　crucial　for　achieving　regional　high-quality　integrated　development.　However,　previous　studies　have　primarily　focused　on　＂attribute　data,＂　neglecting　the　advantages　of　＂relationship　data＂　in　identifying　spatial　correlations　and　the　value　of　network　structure　in　influencing　the　performance　of　＂attribute　data.＂　To　address　this　gap,　this　study　utilizes　panel　data　from　41　cities　in　the　Yangtze　River　Delta　urban　agglomeration　(YRDUA)　from　2010　to　2021　to　examine　the　overall　network　structure　(ONS)　and　individual　network　structure　(INS)　characteristics　of　HQED.　Building　on　this　foundation,　it　further　explores　the　impact　of　SCNS　on　HQED　and　its　heterogeneity.　To　achieve　this　objective,　we　employ　social　network　analysis　(SNA),　panel　data　regression　models,　and　spatial　panel　quantile　regression　(SQR)　models　to　analyze　these　relationships.　The　results　show　that:　(1)　The　overall　network　structure　for　HQED　of　the　YRDUA　remains　relatively　stable,　the　extent　of　correlation　closeness　requires　enhancement.　(2)　The　cities　of　Wuxi,　Suzhou-S,　Shanghai,　Changzhou,　and　Nanjing　occupy　central　network　positions,　functioning　as　＂intermediaries＂　and　＂bridges.＂　(3)　An　increase　in　network　density　and　a　decrease　in　network　efficiency　significantly　improve　the　overall　HQED　level　of　the　YRDUA　and　reduce　internal　differences　within　the　urban　agglomeration.　Furthermore,　degree　centrality,　closeness　centrality,　betweenness　centrality,　in-degree,　and　out-degree　all　significantly　promote　urban　HQED,　with　evident　urban　heterogeneity　in　the　effects　of　individual　network　centrality.　This　finding　enriches　the　theoretical　framework　for　spatial　analysis　for　the　HQED　of　urban　agglomerations　and　provides　valuable　policy　recommendations　to　promote　the　high-quality　integrated　development　of　urban　agglomerations.