TY - GEN
T1 - An ontology-based approach to sentiment classification of mixed opinions in online restaurant reviews
AU - Kim, Hea Jin
AU - Song, Min
PY - 2013
Y1 - 2013
N2 - Consumers review other consumer's opinion and experience of the quality of various products before making purchase. Automatic sentiment analysis of WOM in the form of user product reviews, blog posts and comments in online forum can support strategies in areas such as search engines, recommender systems, and market research and benefit to both consumers and sellers. The ontology-based approach designed in this work aims to investigate how to detect and classify mixed positive and negative opinions by interpreting with an ontology containing opinion information on terms. Our research question is whether disinterested subjectivity scores of sentiment ontology are pertinent to sentiment orientations not affected by reviewer's linguistic bias. The experimental results adopting opinion lexical resource achieve better and more stable performance in F-measure.
AB - Consumers review other consumer's opinion and experience of the quality of various products before making purchase. Automatic sentiment analysis of WOM in the form of user product reviews, blog posts and comments in online forum can support strategies in areas such as search engines, recommender systems, and market research and benefit to both consumers and sellers. The ontology-based approach designed in this work aims to investigate how to detect and classify mixed positive and negative opinions by interpreting with an ontology containing opinion information on terms. Our research question is whether disinterested subjectivity scores of sentiment ontology are pertinent to sentiment orientations not affected by reviewer's linguistic bias. The experimental results adopting opinion lexical resource achieve better and more stable performance in F-measure.
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U2 - 10.1007/978-3-319-03260-3_9
DO - 10.1007/978-3-319-03260-3_9
M3 - Conference contribution
AN - SCOPUS:84892150917
SN - 9783319032597
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 95
EP - 108
BT - Social Informatics - 5th International Conference, SocInfo 2013, Proceedings
T2 - 5th International Conference on Social Informatics, SocInfo 2013
Y2 - 25 November 2013 through 27 November 2013
ER -