The rapid growth of Internet-based applications, such as social media platforms and blogs,
has resulted in comments and reviews concerning day-to-day activities. Sentiment analysis …

Despite the recent success of deep neural networks in natural language processing and
other spheres of artificial intelligence, their interpretability remains a challenge. We analyze …

With accelerated evolution of the internet as websites, social networks, blogs, online portals,
reviews, opinions, recommendations, ratings, and feedback are generated by writers. This …

Sentiment analysis and opinion mining are valuable for extraction of useful subjective
information out of text documents. These tasks have become of great importance, especially …

We describe a state-of-the-art sentiment analysis system that detects (a) the sentiment of
short informal textual messages such as tweets and SMS (message-level task) and (b) 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 …

SenticNet is a publicly available semantic and affective resource for concept-level sentiment
analysis. Rather than using graph-mining and dimensionality-reduction techniques …

Sentiment understanding has been a long-term goal of AI in the past decades. This paper
deals with sentence-level sentiment classification. Though a variety of neural network …

An increasingly large amount of multimodal content is posted on social media websites such
as YouTube and Facebook everyday. In order to cope with the growth of such so much …

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 …