Sentiment Analysis And Polarity Shift According To The Levels Of Polarity

811 Words4 Pages
1.1 Sentiment Analysis Sentiment Analysis and Polarity Shift According to the levels of granularity, tasks in sentiment analysis can be divided into four categorizations: document level, sentence-level, phrase-level, and aspect-level sentiment analysis. Focusing on the phrase/sub sentence and aspect-level sentiment analysis. With the lexicon of words, established prior polarities and identify the “contextual polarity” of phrases, based on some refined annotations. For document and sentence-level sentiment classification , there are two main types of methods in the literature: term-counting and machine learning methods. 1.1.1 Sentiment Polarity and Degrees of Positivity If a given opinionated piece of text, wherein it is assumed…show more content…
This presents us with interesting opportunities to explore the relationships between classes. 1.1.2 Subjectivity Detection and Opinion Identification Work in polarity classification often assumes the incoming documents to be opinionated. For many applications, although, need to decide whether a given document contains subjective information or not, or identify which portions of the document are subjective. Subjectivity detection or ranking at the document level can be thought of as having its roots in studies in genre classification by achieving high accuracy (97%) with a Naive Bayes classifier on a particular corpus . Work in this direction is not limited to the binary distinction between subjective and objective labels. 1.1.3 Joint Topic–Sentiment Analysis One simplifying assumption sometimes made by work on document level sentiment classification is that each document under consideration is focused on the subject matter of interest in the document. This is in part because one can often assume that the document set was created by first collecting only on-topic documents

More about Sentiment Analysis And Polarity Shift According To The Levels Of Polarity

Open Document