Recently, research on short text topic models has addressed the challenges of social media
datasets. These models are typically evaluated using automated measures. However, recent …

Opinion summarization is the task of automatically creating summaries that reflect subjective
information expressed in multiple documents, such as product reviews. While the majority of …

Aspect-based sentiment analysis is a fine-grained sentiment classification task. Recently,
graph neural networks over dependency trees have been explored to explicitly model …

Topic modeling is one of the most powerful techniques in text mining for data mining, latent
data discovery, and finding relationships among data and text documents. Researchers …

Target-oriented sentiment classification aims at classifying sentiment polarities over
individual opinion targets in a sentence. RNN with attention seems a good fit for the …

Aspect level sentiment analysis is a fine-grained task in sentiment analysis. It extracts
aspects and their corresponding sentiment polarity from opinionated text. The first subtask of …

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 …

Aspect extraction is an important and challenging task in aspect-based sentiment analysis.
Existing works tend to apply variants of topic models on this task. While fairly successful …

Opinion mining is considered as a subfield of natural language processing, information
retrieval and text mining. Opinion mining is the process of extracting human thoughts and …

The field of sentiment analysis, in which sentiment is gathered, analyzed, and aggregated
from text, has seen a lot of attention in the last few years. The corresponding growth of the …