Los puntos clave no están disponibles para este artículo en este momento.
This paper presents a phrase pattern-based method in classifying sentiment orientation of text. That is to analyze whether the text expresses a favorable or unfavorable sentiment for a specific subject. In our method, we construct some phrase patterns and calculate their sentiment orientation by unsupervised learning algorithm. When we classify a document, we first add special tags to some words in the text, then match the tags within a sentence with some phrase patterns to get the sentiment orientation of the sentence. At last, we add up the sentiment orientation of each sentence. We classify the text according to this summation. The method achieves an accuracy rate of 86% when used to evaluate sports reviews from some Websites.
Fei et al. (Thu,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: