Aspect Sentiment Model for Micro Reviews
(b) Naver Movie datasets
['Dataset', 'JST', 'ASUM', 'JAST', 'MicroASM']
On all datasets, MicroASM performs the best. JST performs the worst on all datasets except for the Shopping dataset, where ASUM performs worse. One interesting finding is that ASUM, JAST, and MicroASM perform similarly on both English and Korean datasets, however JST performs worse on the Naver datasets. This may mean that on real world micro review datasets, JST performs worse than usual when it is used to normal datasets. Note that the main difference between the Yelp and the Naver datasets is that Naver reviews are forced to be written within a 140-character limit, while Yelp does not impose such constraint. This means that the Yelp dataset is synthetic and the Yelp short reviews are less natural than that of the Naver short reviews. Thus, the observations discussed above are more evident in Naver reviews than in Yelp reviews. On such datasets, MicroASM still performs better than other models, thus is a more appropriate aspect sentiment model for micro reviews.