Due to the diversity of text expressions, the text sentiment classification algorithm based on
semantic understanding is difficult to establish a perfect sentiment dictionary and sentence …

Sentiment classification has attracted increasing interest from natural language processing.
The goal of sentiment classification is to automatically identify whether a given piece of text …

Sentiment recognition analysis is an important method for studying social textual
information. It has an important position in social text analysis and research. However, at …

The traditional Japanese text sentiment classification mainly relies on some domain experts
to classify text sentiment according to their knowledge, which is time-consuming and …

The convolutional neural network (CNN) and long short-term memory (LSTM) network are
adept at extracting local and global features, respectively. Both can achieve excellent …

Thanks to the availability of websites like Twitter, user-generated content is being published
on the Internet every second. Sentiment Classification is one of the most attractive fields in …

The paper first analyzes the correlation between text sentiment values and personality traits,
proves that text sentiment can have a good support effect on user personality prediction …

Sentiment analysis is one of the active research areas in the field of datamining. Machine
learning algorithms are capable to implement sentiment analysis. Due to the capacity of self …

With the advanced tendency of big data, there are billions of text messages posted on the
Internet to express peoples' views and opinions all the time. And with the explosive growth of …

Because of the complexity of human language, text sentiment classification algorithms
mostly have the problem of excessively huge vocabulary due to redundancy. Deep Belief …