The application discloses an organization implicit cooperation relationship recognition and optimization method based on multi-
modal social network mining, comprising the following steps: multi-source cooperation
data acquisition and preprocessing: collecting organization internal mail correspondence records, meeting participation logs,
instant messaging interaction data and
project management system data, anonymizing the data, and retaining department and role labels; constructing a double-level dynamic weighted
directed graph: the node set includes department-level nodes and employee-level nodes, and the two
layers of nodes are connected through membership; the edge set represents the cooperation interaction behavior between nodes, including communication frequency, task association and
information transmission path, the application, by collecting multi-source heterogeneous data (mail correspondence, meeting logs,
instant messaging records,
project management data, etc.), and through anonymization, cleaning and
processing, breaks down the department data dispersion barriers, provides a
complete data basis for cooperation analysis, and avoids the analysis one-sidedness caused by relying on single structured data in the prior art.