Abstract: Enabling dynamic, computer-driven, context-based detection of social network patterns within an input graph representing a social network. A Social Network Aware Pattern Detection (SNAP) system and method utilizes a highly-scalable, computationally efficient integration of social network analysis (SNA) and graph pattern matching. Social network interaction data is provided as an input graph having nodes and edges. The graph illustrates the connections and/or interactions between people, objects, events, and activities, and matches the interactions to a context. A sample graph pattern of interest is identified and/or defined by the user of the application. With this sample graph pattern and the input graph, a computational analysis is completed to (1) determine when a match of the sample graph pattern is found, and more importantly, (2) assign a weight (or score) to the particular match, according to a pre-defined criteria or context.

Abstract: Enabling dynamic, computer-driven, context-based detection of social network patterns within an input graph representing a social network. A Social Network Aware Pattern Detection (SNAP) system and method utilizes a highly-scalable, computationally efficient integration of social network analysis (SNA) and graph pattern matching. Social network interaction data is provided as an input graph having nodes and edges. The graph illustrates the connections and/or interactions between people, objects, events, and activities, and matches the interactions to a context. A sample graph pattern of interest is identified and/or defined by the user of the application. With this sample graph pattern and the input graph, a computational analysis is completed to (1) determine when a match of the sample graph pattern is found, and more importantly, (2) assign a weight (or score) to the particular match, according to a pre-defined criteria or context.