1. A computer-implemented method for network data characterization, comprising: receiving a network event and related content; creating a data message comprising the content and metadata describing the content and the related event; routing the data message to a plurality of analyzers based on the metadata and one or more subscriptions associated with the plurality of analyzers, wherein the plurality of analyzers include at least one machine-learning analyzer; receiving the routed data message and analyzing the content therein to generate characterization results comprising a content classification and an associated confidence percentage; outputting the characterization results of the plurality of analyzers; and comparing the output characterization results against a plurality of criteria to determine subsequent action to take based on the characterization results, wherein: the characterization results include metadata describing one or more of the following: at least one of the plurality of analyzers, the classified content, and the characterization results; and the subscriptions associated with one of the plurality of analyzers includes at least one message type not included in the subscriptions associated with a different one of the plurality of analyzers.