TY - GEN
T1 - Semantic aspect discovery for online reviews
AU - Alam, Md Hijbul
AU - Lee, Sang-Geun
PY - 2012
Y1 - 2012
N2 - The number of opinions and reviews about different products and services is growing online. Users frequently look for important aspects of a product or service in the reviews. Usually, they are interested in semantic (i.e., sentiment-oriented) aspects. However, extracting semantic aspects with supervised methods is very expensive. We propose a domain independent unsupervised model to extract semantic aspects, and conduct qualitative and quantitative experiments to evaluate the extracted aspects. The experiments show that our model effectively extracts semantic aspects with correlated top words. In addition, the conducted evaluation on aspect sentiment classification shows that our model outperforms other models by 5-7% in terms of macro-average F1.
AB - The number of opinions and reviews about different products and services is growing online. Users frequently look for important aspects of a product or service in the reviews. Usually, they are interested in semantic (i.e., sentiment-oriented) aspects. However, extracting semantic aspects with supervised methods is very expensive. We propose a domain independent unsupervised model to extract semantic aspects, and conduct qualitative and quantitative experiments to evaluate the extracted aspects. The experiments show that our model effectively extracts semantic aspects with correlated top words. In addition, the conducted evaluation on aspect sentiment classification shows that our model outperforms other models by 5-7% in terms of macro-average F1.
KW - Aspect discovery
KW - Opinion mining
KW - Sentiment analysis
KW - Topic model
UR - http://www.scopus.com/inward/record.url?scp=84874104662&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874104662&partnerID=8YFLogxK
U2 - 10.1109/ICDM.2012.65
DO - 10.1109/ICDM.2012.65
M3 - Conference contribution
AN - SCOPUS:84874104662
SN - 9780769549057
T3 - Proceedings - IEEE International Conference on Data Mining, ICDM
SP - 816
EP - 821
BT - Proceedings - 12th IEEE International Conference on Data Mining, ICDM 2012
T2 - 12th IEEE International Conference on Data Mining, ICDM 2012
Y2 - 10 December 2012 through 13 December 2012
ER -