Lsislif: Feature Extraction and Label Weighting for Sentiment Analysis in Twitter

Lsislif: CRF and Logistic Regression for Opinion Target Extraction and Sentiment Polarity Analysis

Unified Feature and Instance Based Domain Adaptation for Aspect-Based Sentiment Analysis

The supervised models for aspect-based sentiment analysis (ABSA) rely heavily on labeled data. However, fine-grained labeled data are scarce for the ABSA task. To alleviate the dependence on labeled data, prior works mai…

A Study of Feature Extraction techniques for Sentiment Analysis

Sentiment Analysis refers to the study of systematically extracting the meaning of subjective text . When analysing sentiments from the subjective text using Machine Learning techniques,feature extraction becomes a signi…

Multi-Label Sentiment Analysis on 100 Languages with Dynamic Weighting for Label Imbalance

We investigate cross-lingual sentiment analysis, which has attracted significant attention due to its applications in various areas including market research, politics and social sciences. In particular, we introduce a s…

Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture

The World Wide Web holds a wealth of information in the form of unstructured texts such as customer reviews for products, events and more. By extracting and analyzing the expressed opinions in customer reviews in a fine-…