Abstract: This article focuses on 72 industrial heritage sites in Shenyang City， using digital footprints as a starting point， data collection using octopus collectors， and combining ROST CM6’s word frequency and social network analysis functions， as well as UCINET’s centrality， structural holes， network density， and cohesive subgroup analysis methods， to deeply explore the tourist attention， development status， and co-occurrence network characteristics of Shenyang’s industrial heritage network. The research results show that：1） significant difference in attention. The attention to industrial heritage in Shenyang shows obvious differences and regularity.2） highlight of core nodes. In the social network co-occurrence of industrial heritage， nodes located at the core of the network are highly consistent with industrial heritage that ranks high in attention.3） difficulty in connection. There are significant difficulties in connecting various industrial heritage sites with other heritage nodes， with 50 heritage sites isolated in the network. The overall heritage network exhibits the characteristics of "large dispersion， small aggregation".4） construction of networked spatial structure. To break the current dilemma， this article proposes to construct a networked spatial structure with "two cores， nine nodes， and seven zones" as the core， aiming to promote the optimization and upgrading of Shenyang’s industrial heritage network through multi line connection， core node radiation guidance， and multi cluster integrated development， explore new paths for industrial heritage protection and utilization， and promote the sustainable development and industrial cultural revival of Shenyang.