Patent ID: 7739211

Claim:
A computer-implemented method comprising: receiving a data set of social network interactions and communications data of multiple participants or actors; configuring social network analysis (SNA) metrics and tolerances, wherein the tolerances enable dynamic SNA of what is within a normal range of communication activity/patterns/behavior over a period of time; converting the data set to a graphical representation containing a node for each participant among the multiple participants; computing SNA metrics values for each node within the graphical representation; determining, via use of a plurality of SNA metrics, when the metric value computed for a particular data point within the data set falls outside of a dynamically determined normal range bounded by the tolerances, wherein said determining automatically identifies abnormal events in a provided communication pattern and utilizes unsupervised learning techniques for identification of normal or abnormal behavior, wherein complex aspects of communication patterns identified within the data set are converted into a variety of simple numerical measures and wherein graphical structures are converted into numerical values utilizing SNA metrics; and tagging the particular data point whose behavior falls outside the dynamically determined normal range as an anomaly.