Network　science　has　been　widely　applied　in　theoretical　and　empirical　studies　of　global　value　chain　(GVC),　and　many　related　articles　have　emerged,　forming　many　more　mature　and　complete　analytical　frameworks.　Among　them,　the　GVC　accounting　method　based　on　complex　network　theory　is　different　from　the　mainstream　economics　in　both　research　angle　and　content.　In　this　paper,　we　build　up　global　industrial　value　chain　network　(GIVCN)　models　based　on　World　Input-Output　Database,　introduce　the　theoretical　framework　of　Social　Capital,　and　define　the　network-based　indicators　with　economic　meanings.　Second,　we　follow　the　econometric　framework　to　analyze　the　hypothesis　and　test　whether　it　is　true.　Finally,　we　study　how　the　three　types　of　capital　constituted　by　these　indicators　interact　with　each　other,　and　discuss　their　impact　on　the　social　capital　(economic　development　level,　i.e.,　GDP).　The　results　prove　that　the　structural　capital　(industrial　status)　has　a　positive　impact　on　the　social　capital;　the　relational　capital　(industrial　correlation)　has　a　positive　impact　on　both　social　capital　and　structural　capital;　the　cognitive　capital　(industrial　structure)　has　a　small　impact　on　the　social　capital,　structural　capital,　and　relational　capital.