11. A computer-implemented system for providing default hierarchical training for social indexing, comprising: an electronic database, comprising: articles of digital information maintained for social indexing; and a hierarchically-structured tree of topics, which each comprise a label comprising one or more words; a processor and memory within which code for execution by the processor is stored, further comprising: an electronically-stored rules set identifying hard constraints based on the labels comprised in the topic tree and the topic tree's hierarchical structure, wherein the hard constraints are defined to include required immutable rules comprising at least one of: that a topic model comprises a single term comprised from a label that is duplicated within the topic tree; that a topic model includes no term from the label for the topic to which the topic model belongs; and when the label is duplicated within the topic tree, that a topic model includes no term from the label of a parent topic for the topic to which the topic model belongs; a topic builder module that, for each topic in the topic tree, creates a topic model subject to the hard constraints, the topic model comprising a finite state pattern that comprises a pattern evaluable against the articles; and an evaluator module evaluating the topic models for the topic tree against the hard constraints, and disfavoring those topic models that violate one or more of the immutable rules; and a user interface visually identifying for each topic, the topic model, which best satisfies the constraints.
11. A computer-implemented system for providing default hierarchical training for social indexing, comprising: an electronic database, comprising: articles of digital information maintained for social indexing; and a hierarchically-structured tree of topics, which each comprise a label comprising one or more words; a processor and memory within which code for execution by the processor is stored, further comprising: an electronically-stored rules set identifying hard constraints based on the labels comprised in the topic tree and the topic tree's hierarchical structure, wherein the hard constraints are defined to include required immutable rules comprising at least one of: that a topic model comprises a single term comprised from a label that is duplicated within the topic tree; that a topic model includes no term from the label for the topic to which the topic model belongs; and when the label is duplicated within the topic tree, that a topic model includes no term from the label of a parent topic for the topic to which the topic model belongs; a topic builder module that, for each topic in the topic tree, creates a topic model subject to the hard constraints, the topic model comprising a finite state pattern that comprises a pattern evaluable against the articles; and an evaluator module evaluating the topic models for the topic tree against the hard constraints, and disfavoring those topic models that violate one or more of the immutable rules; and a user interface visually identifying for each topic, the topic model, which best satisfies the constraints. 14. A system according to claim 11 , wherein the processor and memory further comprise: an article matching evaluation module counting the articles that are matched by each of the topic models, and favoring those topic models proportionately matching a percentage of the articles closest to an ideal percentage.