Using Verbs and Adjectives to Automatically Classify Blog Sentiment

Paula Chesley, Bruce Vincent, Li Xu, Rohini Srihari

This paper presents experiments on subjectivity and polarity classifications of topic- and genre-independent blog posts, making novel use of a linguistic feature, verb class information, and of an online resource, the Wikipedia dictionary, for determining the polarity of adjectives. Each post from a blog is classified as objective, positive, or negative. Our method of determining the polarity of adjectives has an accuracy rate of 90.9%. Accuracy rates of two verb classes demonstrating polarity are 89.3% and 91.2%. Initial classifier results show blog-post accuracies with significant increases above the established baseline classification.


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