The ever-increasing number of Internet users and online services, such as Amazon, Twitter
and Facebook has rapidly motivated people to not just transact using the Internet but to also …

Aspect-level sentiment classification aims at identifying the sentiment polarity of specific
target in its context. Previous approaches have realized the importance of targets in …

Aspect-level sentiment classification is a finegrained task in sentiment analysis. Since it
provides more complete and in-depth results, aspect-level sentiment analysis has received …

Deep learning techniques for Sentiment Analysis have become very popular. They provide
automatic feature extraction and both richer representation capabilities and better …

The ways people use language can reveal clues to their emotions, social behaviours,
thinking styles, cultures and the worlds around them. In the past two decades, research at …

Aspect-level sentiment analysis aims to distinguish the sentiment polarity of each specific
aspect term in a given sentence. Both industry and academia have realized the importance …

Aspect-based sentiment analysis technologies may be a very practical methodology for
securities trading, commodity sales, movie rating websites, etc. Most recent studies adopt …

Lexical resources are widely popular in the field of Sentiment Analysis, as they represent a
resource that directly encodes sentimental knowledge. Usually sentiment lexica are used for …

We propose a novel approach to sentiment analysis for a low resource setting. The intuition
behind this work is that sentiment expressed towards an entity, targeted sentiment, may be …

Sentiment dictionary is of great value to sentiment analysis, which is used widely in
sentiment analysis compositionality. However, the sentiment polarity and intensity of the …