1. A method for graphically characterizing statements about an object, comprising: applying, as a result of computing hardware and programmable memory, frame extraction, to a first corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; identifying, as a result of computing hardware and programmable memory, a first object-specific corpus, that is a subset of the first corpus, where all the statements of the first object-specific corpus are about a same first object; categorizing, as a result of computing hardware and programmable memory, a sentiment of each statement, of the first object-specific corpus; categorizing a polarity of each statement, of the first object-specific corpus; categorizing an intensity of each statement, of the first object-specific corpus; determining, as a result of computing hardware and programmable memory, a net polarity measure as a function of the polarity categorization and a net intensity measure as a function of the intensity categorization; producing, as a result of computing hardware and programmable memory, a first graphical representation, of the first object-specific corpus; placing the first graphical representation, relative to a first axis, in accordance with the net polarity measure; and placing the first graphical representation, relative to a second axis, in accordance with the net intensity measure.
12. The method of claim 1 , further comprising: producing a second corpus, containing statements within a second temporal range that is different from a first temporal range of the statements of the first corpus; applying frame extraction, to the second corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; identifying a second object-specific corpus, that is a subset of the second corpus, where all the statements of the second object-specific corpus are about the same first object as the first object-specific corpus; categorizing the sentiment of each statement, of the second object-specific corpus; determining a net metric value as a function of the categorization of the second object-specific corpus; and producing a second graphical representation, of the second object-specific corpus, that is placed according to the second net metric.