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 …

Social media is playing a growing role in elections world-wide. Thus, automatically
analyzing electoral tweets has applications in understanding how public sentiment is …

The rapid growth in web development has transformed today's communication. The
combination of features and corresponding sentiment words (SWs) can help produce …

Recent advances in machine learning have led to computer systems that are humanlike in
behavior. Sentiment analysis, the automatic determination of emotions in text, is allowing us …

A vast majority of the work in Sentiment Analysis has been on developing more accurate
sentiment classifiers, usually involving supervised machine learning algorithms and a …

Linguistic research on multilingual societies has indicated that there is usually a preferred
language for expression of emotion and sentiment (Dewaele, 2010). Paucity of data has …

Code-switching or the juxtaposition of linguistic units from two or more languages in a single
utterance, has, in recent times, become very common in text, thanks to social media and …

The huge amount of subjective data available on the web carrying people's opinions,
sentiments and beliefs, is an important resource for companies and merchants who want to …

A vast number of user opinions are available from reviews posted on e-commerce websites.
Although these opinions are a valuable source of knowledge for both manufacturers and …

Customer reviews include opinions of the customer who purchased the products and
expressed opinions may be regarding their satisfaction and criticism about different features …