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 from text consists of extracting information about opinions, sentiments,
and even emotions conveyed by writers towards topics of interest. It is often equated to …

The state-of-the-art methods in aspect-level sentiment classification have leveraged the
graph based models to incorporate the syntactic structure of a sentence. While being …

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions,
sentiments, evaluations, attitudes, and emotions from written language. It is one of the most …

We present a lexicon-based approach to extracting sentiment from text. The Semantic
Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic …

A huge number of informal messages are posted every day in social network sites, blogs,
and discussion forums. Emotions seem to be frequently important in these texts for …

Sentiment analysis is the computational study of people's opinions, sentiments, emotions,
moods, and attitudes. This fascinating problem offers numerous research challenges, but …

Textual information in the world can be broadly categorized into two main types: facts and
opinions. Facts are objective expressions about entities, events and their properties …

An important part of our information-gathering behavior has always been to find out what
other people think. With the growing availability and popularity of opinion-rich resources …

With the rapid development and popularization of Internet and mobile communication
technologies, text data mining has attracted much attention. In particular, with the wide use …