TY - GEN
T1 - Using verbs and adjectives to automatically classify blog sentiment
AU - Chesley, Paula
AU - Vincent, Bruce
AU - Xu, Li
AU - Srihari, Rohini K.
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/33747159833
M3 - Conference contribution
AN - SCOPUS:33747159833
SN - 1577352645
SN - 9781577352648
T3 - AAAI Spring Symposium - Technical Report
SP - 27
EP - 29
BT - Computational Approaches to Analyzing Weblogs - Papers from the AAAI Spring Symposium, Technical Report
T2 - 2006 AAAI Spring Symposium
Y2 - 27 March 2006 through 29 March 2006
ER -