Unsupervised Sentiment Analysis

Question

I\'ve been reading a lot of articles that explain the need for an initial set of texts that are classified as either \'positive\' or \'negative\' before a sentiment analysis

Answer 1

A classic paper by Peter Turney (2002) explains a method to do unsupervised sentiment analysis (positive/negative classification) using only the words excellent and poor as a seed set. Turney uses the mutual information of other words with these two adjectives to achieve an accuracy of 74%.