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Sentiment extraction is a very difficult NLP problem, mainly because algorithms must uncover subjective human emotions, that are often mixed, subtle, marked by irony.. Even a human reading subjective text can have a hard time quantifying the polarity of the opinion (what is a 20% positive opinion, or a 90% negative opinion)?
NLP subproblems: negation, segmentation (which words refer to which entity), anaphora (cross-references)
- Supervised (annotated corpora)
- Unsupervised (dictionaries)