10. An apparatus operable to provide at least one sentiment classifier based on a plurality of features, the apparatus comprising: a feature extraction component, implemented by at least one processing device, operable to extract the plurality of features from training data, wherein the training data comprises a plurality of units, the feature extraction component comprising: a part-of-speech (PoS) sub-component operable to label at least one element of each unit of the training data according to a plurality of PoS tags to provide PoS features; a dictionary sub-component operable to: check at least one element of each unit of the training data according to a plurality of dictionaries to provide dictionary features; and a negation/inversion sub-component operable to detect a plurality of negation/inversion elements in the training data to provide a plurality of negation/inversion features based on a negation dictionary and an inversion dictionary of the plurality of dictionaries, and operable to label at least one element after each of the plurality of negation/inversion features to provide negated/inverted elements features based on at least one of a propagation window or punctuation in the training data; a feature value determination component, implemented by the at least one processing device and operatively connected to the feature extraction component, operable to determine a value for each feature of the plurality of features based on a frequency at which each feature occurs in the training data; a class labeling component, implemented by the at least one processing device, operable to label each unit of the training data according to a plurality of sentiment classes to provide labeled training data; and a sentiment classifier generation component, implemented by the at least one processing device and operatively connected to the feature value determination component and the class labeling component, operable to provide the at least one sentiment classifier based on the value of each feature of the plurality of features and the labeled training data using a supervised classification technique.
10. An apparatus operable to provide at least one sentiment classifier based on a plurality of features, the apparatus comprising: a feature extraction component, implemented by at least one processing device, operable to extract the plurality of features from training data, wherein the training data comprises a plurality of units, the feature extraction component comprising: a part-of-speech (PoS) sub-component operable to label at least one element of each unit of the training data according to a plurality of PoS tags to provide PoS features; a dictionary sub-component operable to: check at least one element of each unit of the training data according to a plurality of dictionaries to provide dictionary features; and a negation/inversion sub-component operable to detect a plurality of negation/inversion elements in the training data to provide a plurality of negation/inversion features based on a negation dictionary and an inversion dictionary of the plurality of dictionaries, and operable to label at least one element after each of the plurality of negation/inversion features to provide negated/inverted elements features based on at least one of a propagation window or punctuation in the training data; a feature value determination component, implemented by the at least one processing device and operatively connected to the feature extraction component, operable to determine a value for each feature of the plurality of features based on a frequency at which each feature occurs in the training data; a class labeling component, implemented by the at least one processing device, operable to label each unit of the training data according to a plurality of sentiment classes to provide labeled training data; and a sentiment classifier generation component, implemented by the at least one processing device and operatively connected to the feature value determination component and the class labeling component, operable to provide the at least one sentiment classifier based on the value of each feature of the plurality of features and the labeled training data using a supervised classification technique. 16. The apparatus of claim 10 , further comprising: a taxonomy generation component, implemented by the at least one processing device and operatively connected to the sentiment classifier generation component, operable to: provide a plurality of sentiment classifiers based on a plurality of sets of training data, the plurality of sets of training data being associated with a plurality of subjects; associate each sentiment classifier of the plurality of sentiment classifiers with one of the plurality of subjects; and provide a taxonomy of sentiment classifiers based on a subject, of the plurality of subjects, associated with each sentiment classifier of the plurality of sentiment classifiers.