From the last twenty years, the application of Internet based technologies had brought a
significant impact on the Indian stock market. Use of the Internet has eliminated the barriers …

The polarity shift problem is a major factor that affects classification performance of machine-
learning-based sentiment analysis systems. In this paper, we propose a three-stage …

Although deep neural networks are excellent for text sentiment analysis, their applications in
real-world practice are occasionally limited owing to their black-box property. In this study …

Sentiment analysis is a process of identifying and categorizing opinions expressed in a
piece of text. It classifies the text into positive, negative or neutral. Lexicon-based and …

The present paper studies the scope of sentiment analysis on news articles on impact of
economic downfall of the primary international stock markets, comparing it with that of …

In the history of mankind, no disease as virulent as the Novel Corona Virus (COVID-19) has
forced global pandemonium. As the world's nations band together to fight this disease and …

The way of expressing sentiment (− ve/+ ve) in the form of textual information depends on
the way of thinking of human beings. Identifying aspect extraction and sentiment polarity …

The paper introduces PolaritySim–a novel approach to disambiguating context-dependent
sentiment polarity of words. The task of resolving the polarity of a given word instance as …

Word-level contextual sentiment analysis (WCSA) is an important task for mining reviews or
opinions. When analyzing this type of sentiment in the industry, both the interpretability and …

Annually, over three million people in North America suffer concussions. Every age group is
susceptible to concussion, but youth involved in sporting activities are particularly …