Social media is a powerful source of communication among people to share their sentiments
in the form of opinions and views about any topic or article, which results in an enormous …

In literature, the machine learning-based studies of sentiment analysis are usually
supervised learning which must have pre-labeled datasets to be large enough in certain …

In recent years, the explosive growth of online media, such as blogs and social networking
sites, has enabled individuals and organizations to write about their personal experiences …

Online media, such as blogs and social networking sites, generate massive volumes of
unstructured data of great interest to analyze the opinions and sentiments of individuals and …

Sentiment analysis (SA) is the computational analysis of the ideas, feelings, and opinions
that determines the polarity of the text documents or comments using natural language …

This paper describes in detail the approach carried out by the GTI research group for
SemEval 2016 Task 5: Aspect-Based Sentiment Analysis, for the different subtasks …

The collection, detection and monitoring of information such as side effects, adverse effects,
warnings, precautions of pharmaceutical products is a challenging task. With the advent of …

With the evolution of Social Networks (SNs) such as Twitter, millions of users can interacting,
sharing interests, activities, contents or exchanging experiences and opinions. Sharing …

Micro-blogging sources such as the Twitter social network provide valuable real-time data
for market prediction models. Investors' opinions in this network follow the fluctuations of the …

Text sentiment classification in aspect level is one of the hottest research topics in the field of
natural language processing. The purpose of the aspect-level sentiment analysis is to …