1. A non-transitory computer readable medium carrying instructions for a sentiment classifier for sentiment classification of content comprising: an aspect classifier configured to classify content as being related to a particular aspect of a plurality of aspects of information, the aspect classifier incorporating at least a portion of a domain specific sentiment lexicon to assist in classifying the content, wherein the domain specific sentiment lexicon is configured by: (i) domain specific words and/or phrases from an annotated corpus which has been filtered, (ii) domain specific words and/or phrases obtained via a search of the world wide web using a predetermined linguistic pattern and filtering the returned search results, and (iii) domain specific words and/or phrases obtained via a dictionary expansion technique performed on the domain specific words and/or phrases obtained by at least one of (i) or (ii); a polarity classifier configured to classify the content classified by the aspect classifier as having one of a positive sentiment of the particular aspect of information, a negative sentiment of the particular aspect of information or as having no sentiment of the particular aspect of information, the polarity classifier incorporating at least a portion of the domain specific sentiment lexicon to assist in classifying the content; and an aggregator configured to receive and aggregate results of predictions generated by the aspect classifier and results of predictions generated by the polarity classifier.
1. A non-transitory computer readable medium carrying instructions for a sentiment classifier for sentiment classification of content comprising: an aspect classifier configured to classify content as being related to a particular aspect of a plurality of aspects of information, the aspect classifier incorporating at least a portion of a domain specific sentiment lexicon to assist in classifying the content, wherein the domain specific sentiment lexicon is configured by: (i) domain specific words and/or phrases from an annotated corpus which has been filtered, (ii) domain specific words and/or phrases obtained via a search of the world wide web using a predetermined linguistic pattern and filtering the returned search results, and (iii) domain specific words and/or phrases obtained via a dictionary expansion technique performed on the domain specific words and/or phrases obtained by at least one of (i) or (ii); a polarity classifier configured to classify the content classified by the aspect classifier as having one of a positive sentiment of the particular aspect of information, a negative sentiment of the particular aspect of information or as having no sentiment of the particular aspect of information, the polarity classifier incorporating at least a portion of the domain specific sentiment lexicon to assist in classifying the content; and an aggregator configured to receive and aggregate results of predictions generated by the aspect classifier and results of predictions generated by the polarity classifier. 2. The sentiment classifier of claim 1 wherein the aspect classifier further incorporates a general purpose sentiment lexicon.