System and method of computational social network development environment for human intelligence

A computer-implemented method for supporting human intelligence, comprising an act of:

• causing a data processor to execute instructions stored on a non-transitory memory such that upon execution, the data processor performs operations of:
• detecting changes in a plurality of social relations among users within a dynamic information network comprising a plurality of data;
• and
• enabling, understanding, of a current social situation in the dynamic information network through a plurality of integrated modules, wherein the plurality of integrated modules comprises:
• an active network mining module, wherein the active network mining module identifies incomplete data that is related to at least one change in the plurality of social relations, and wherein the active network mining module further resolves conflicting and missing data in the dynamic information network to derive a set of trustworthiness relations using link analysis;
• a relevant network discovery module, wherein the relevant network discovery module constructs a relevant network, comprising, nodes and clusters of nodes, from hidden relations within the dynamic information network;
• an information-aware social network module for constructing an information-aware social network using the relevant network, wherein the information-aware social network composes a plurality of items of interest, and wherein the information-aware social network module further classifies and prioritizes the plurality of items of interest to provide an assessment of a current social situation to a user;
• wherein a node is associated with a set of perceived importance scores and a set of rank scores;
• wherein the active network mining module utilizes an information imbalance measure to prioritize data for efficient data collection;
• and
• computing the information imbalance measure of the node from the set of perceived importance scores of the node and the set of rank scores of the node, wherein the information imbalance measure reflects an inconsistency within and between the set of perceived importance scores of the node and the set of rank scores of the node.

A computer program product for supporting human intelligence analysis, the computer program product comprising computer-readable instructions stored on a non-transitory computer-readable medium that are executable by a computer having, a processor for causing the processor to perform operations of:

• detecting changes in a plurality of social relations among users within a dynamic information network comprising a plurality of data;
• and
• enabling understanding of a current social situation in the dynamic information network through a plurality of integrated modules, wherein the plurality of integrated modules comprises:
• an active network mining module, wherein the active network mining module identifies incomplete data that is related to at least one change in the plurality of social relations, and wherein the active network mining module further resolves conflicting and missing data in the dynamic information network to derive a set of trustworthiness relations using link analysis;
• a relevant network discovery module, wherein the relevant network discovery module constructs a relevant network, comprising nodes and clusters of nodes, from hidden relations within the dynamic information network;
• an information-aware social network module for constructing an information-aware social network using the relevant network, Wherein the information-aware social network comprises a plurality of items of interest, and wherein the information-aware social network module further classifies and prioritizes the plurality of items of interest to provide an assessment of a current social situation to a user;
• wherein a node is associated with a set of perceived importance scores and a set of rank scores;
• wherein the active network mining module utilizes an information imbalance measure to prioritize data for efficient data collection;
• and
• computing the information imbalance measure of the node from the set of perceived importance scores of the node and the set of rank scores of the node, wherein the information imbalance measure reflects an inconsistency within and between the set of perceived importance scores of the node and the set of rank scores of the node.