Abstract: Rapid increase in internet users along with growing power of online review sites
and social media has given birth to Sentiment analysis or Opinion mining, which aims at …

In this paper, based on more than ten years' studies on this dedicated research thrust, a
comprehensive review concerning information mining from big consumer opinion data in …

In this paper, we present the first deep learning approach to aspect extraction in opinion
mining. Aspect extraction is a subtask of sentiment analysis that consists in identifying …

In order to recommend products to users we must ultimately predict how a user will respond
to a new product. To do so we must uncover the implicit tastes of each user as well as the …

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 …

Sentiment analysis or opinion mining is the computational study of people's opinions,
appraisals, attitudes, and emotions toward entities, individuals, issues, events, topics and …

We present a neural framework for opinion summarization from online product reviews
which is knowledge-lean and only requires light supervision (eg, in the form of product …

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

Sentiment classification aims to automatically predict sentiment polarity (eg, positive or
negative) of users publishing sentiment data (eg, reviews, blogs). Although traditional …

In this paper, we define and study a new opinionated text data analysis problem called
Latent Aspect Rating Analysis (LARA), which aims at analyzing opinions expressed about …