As the prevalence of social media on the Internet, opinion mining has become an essential
approach to analyzing so many data. Various applications appear in a wide range of …

Sentiment analysis (also known as opinion mining) is an active research area in natural
language processing. It aims at identifying, extracting and organizing sentiments from user …

Along with the emergence of the Internet, the rapid development of handheld devices has
democratized content creation due to the extensive use of social media and has resulted in …

Accurate detection of emotion from natural language has applications ranging from building
emotional chatbots to better understanding individuals and their lives. However, progress on …

This paper deals with the aspect-level sentiment classification which identifies the sentiment
polarity of a specific aspect of its context. We introduce novel attention networks by using the …

Sentiment analysis is the task of automatically determining from text the attitude, emotion, or
some other affectual state of the author. This chapter summarizes the diverse landscape of …

A word's sentiment depends on the domain in which it is used. Computational social science
research thus requires sentiment lexicons that are specific to the domains being studied. We …

Target-dependent sentiment analysis on Twitter has attracted increasing research attention.
Most previous work relies on syntax, such as automatic parse trees, which are subject to …

Neural network methods have achieved promising results for sentiment classification of text.
However, these models only use semantics of texts, while ignoring users who express the …

Sentiment analysis, which refers to the task of detecting whether a textual item (eg, a product
review and a blog post) expresses a positive or negative opinion in general or about a given …