Transcription of CHAPTER Naive Bayes and Sentiment Classification
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CHAPTER Naive Bayes and Sentiment Classification
Speech and Language Processing. Daniel Jurafsky & James H. Martin. Copyright 2021. Allrights reserved. Draft of December 29, Bayes and SentimentClassificationClassificationlie s at the heart of both human and machine intelligence. Decidingwhat letter, word, or image has been presented to our senses, recognizing facesor voices, sorting mail, assigning grades to homeworks; these are all examples ofassigning a category to an input. The potential challenges of this task are highlightedby the fabulist Jorge Luis Borges (1964), who imagined classifying animals into:(a) those that belong to the Emperor, (b) embalmed ones, (c) those thatare trained, (d) suckling pigs, (e) mermaids, (f) fabulous ones, (g) straydogs, (h) those that are included in this classification, (i) those thattremble as if they were mad, (j) innumerable ones, (k) those drawn witha very fine camel s hair brush, (l) others, (m) those that have just brokena flower vase, (n) those that resemble flies from a language processing tasks involve classification, although luckily our classesare much easier to define than those of Borges.
sentiment toward a candidate or political action. Extracting consumer or public sen-timent is thus relevant for fields from marketing to politics. The simplest version of sentiment analysis is a binary classification task, and the words of the review provide excellent cues. Consider, for example, the follow-
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