1. A computer-implemented method for isolating desired content, metadata, or both from social media, the method characterized by the steps of: providing a live website, a static harvest of a website, or both, through communications circuitry, storage media, or both, the website comprising one or more content-rich pages; parsing each of the content-rich pages to obtain a language-independent representation comprising a hierarchical structure of one or more nodes; generating a node representation for each of the nodes, the node representation comprising a computer-readable expression stored in memory circuitry; generating a feature vector for each node of the language-independent representation; assigning a label to each node representation according to a schema by executing a trained classification algorithm on the feature vectors of the content-rich pages using processing circuitry, the schema comprising one or more schema elements, each schema element corresponding to a label; gathering, for each schema element, all node representations having matching labels; electing from among the node representations having matching labels one node representation to assign to a schema element field in a template; and applying the template to extract the desired content, metadata, or both according to the schema from all of the content-rich pages.
8. The method of claim 1 , wherein said generating a feature vector further comprises devaluing language type as a feature relative to other features.