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 …

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

Opinion entity extraction is a fundamental task in fine-grained opinion mining. Related
studies generally extract aspects and/or opinion expressions without recognizing the …

Sentiment analysis (SA) has become one of the most active and progressively popular areas
in information retrieval and text mining due to the expansion of the World Wide Web (WWW) …

In this paper, we propose to build large-scale sentiment lexicon from Twitter with a
representation learning approach. We cast sentiment lexicon learning as a phrase-level …

Aspect extraction is an important task in sentiment analysis. Topic modeling is a popular
method for the task. However, unsupervised topic models often generate incoherent …

Sentiment analysis, which addresses the computational treatment of opinion, sentiment, and
subjectivity in text, has received considerable attention in recent years. In contrast to the …

We present a simple but effective method for aspect identification in sentiment analysis. Our
unsupervised method only requires word embeddings and a POS tagger, and is therefore …

Extracting aspect terms and opinion terms are two fundamental tasks in opinion mining. The
recent success of deep learning has inspired various neural network architectures, which …

Motivated by the role of product features in enabling personalized recommendations and
marketing, this research aims to extract product features from online consumer reviews …