Posted: 3 May 2019
Date Written: March 2019
Sentiment analysis labels a body of text as expressing either a positive or negative opinion, as in summarizing the content of an online product review. In this sense, sentiment analysis can be considered the challenge of building a classifier from text. Sentiment analysis can be done by counting the words from a dictionary of emotional terms, by fitting traditional classifiers such as logistic regression to word counts, or, most recently, by employing sophisticated neural networks. These methods progressively improve classification at the cost of increased computation and reduced transparency. A common sentiment analysis task, the classification of IMDb (Internet Movie Database) movie reviews, is used to illustrate the methods on a common task that appears frequently in the literature.
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