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There are so many ways you could go about this. For starters, you could use Conditional Random Fields (CRF). There is a sweet implementation in Python. In which you can set the POS features and more. There is a website from the same source you posted on how to use CRF for your purpose (I have not read it thoroughly). Spacy is another great resource to get ...


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In a truly unsupervised setting, the only possibility is to cluster the documents. Typically this would be done with topic modelling. Then the result could be evaluated by inspecting the words most associated with every topic, and assign a sentiment class to the whole topic/cluster, i.e. all the documents labelled with it.


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