3. A non-transitory computer readable medium having stored thereon instructions for optimizing sentiment evaluation comprising machine executable code which when executed by a processor, causes the processor to perform steps comprising: performing a classification analysis on a first post received for sentiment evaluation to determine a first sentiment classification; receiving a second sentiment classification related to the first post from at least one user; and updating the classification analysis when the first sentiment classification does not match the second sentiment classification, wherein the updating the sentiment classification analysis comprises: plotting the first post in a multidimensional feature space, wherein each dimension in the multidimensional feature space represents a unique feature corresponding to the first post; performing a neighborhood operation for the first post to identify a pattern space in the multidimensional feature space containing a plurality of posts associated with the first post; and applying the second sentiment classification to the plurality of posts in the pattern space, wherein the plurality of posts in the pattern space provide updated training data for the classification analysis.
3. A non-transitory computer readable medium having stored thereon instructions for optimizing sentiment evaluation comprising machine executable code which when executed by a processor, causes the processor to perform steps comprising: performing a classification analysis on a first post received for sentiment evaluation to determine a first sentiment classification; receiving a second sentiment classification related to the first post from at least one user; and updating the classification analysis when the first sentiment classification does not match the second sentiment classification, wherein the updating the sentiment classification analysis comprises: plotting the first post in a multidimensional feature space, wherein each dimension in the multidimensional feature space represents a unique feature corresponding to the first post; performing a neighborhood operation for the first post to identify a pattern space in the multidimensional feature space containing a plurality of posts associated with the first post; and applying the second sentiment classification to the plurality of posts in the pattern space, wherein the plurality of posts in the pattern space provide updated training data for the classification analysis. 15. The medium as set forth in claim 3 further comprising: receiving a strength indication of the second sentiment classification from the user; performing the neighborhood operation based on the strength indication.