The increasing volume of user-generated content on the web has made sentiment analysis
an important tool for the extraction of information about the human emotional state. A current …

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 …

As an important fine-grained sentiment analysis problem, aspect-based sentiment analysis
(ABSA), aiming to analyze and understand people's opinions at the aspect level, has been …

Due to their inherent capability in semantic alignment of aspects and their context words,
attention mechanism and Convolutional Neural Networks (CNNs) are widely applied for …

Aspect-based sentiment analysis (ABSA), which aims to identify fine-grained opinion polarity
towards a specific aspect, is a challenging subtask of sentiment analysis (SA). In this paper …

We propose a novel framework based on neural networks to identify the sentiment of
opinion targets in a comment/review. Our framework adopts multiple-attention mechanism to …

We introduce a deep memory network for aspect level sentiment classification. Unlike
feature-based SVM and sequential neural models such as LSTM, this approach explicitly …

Aspect based sentiment analysis (ABSA) can provide more detailed information than
general sentiment analysis, because it aims to predict the sentiment polarities of the given …

Here for the first time we present a shared task on detecting stance from tweets: given a
tweet and a target entity (person, organization, etc.), automatic natural language systems …

Research on machine assisted text analysis follows the rapid development of digital media,
and sentiment analysis is among the prevalent applications. Traditional sentiment analysis …