Sentiment analysis (SA) of natural language text is an important and challenging task for
many applications of Natural Language Processing. Till now, researchers have used …

The rise of social media is enabling people to freely express their opinions about products
and services. The aim of sentiment analysis is to automatically determine subject's sentiment …

Analyzing and understanding the sentiments of social media documents on Twitter,
Facebook, and Instagram has become a very important task at present. Analyzing the …

With explosive development of the World Wide Web, an enormous amount of text
information containing users' feeling, emotions and opinions has been generated and is …

An integrated deep learning paradigm for the analysis of document-based sentiments is
presented in this article. Generally, sentiment analysis has enormous applications in the real …

This paper presents a detailed review of deep learning techniques used in Sentiment
Analysis. Sentiment analysis is one of the most researched areas in natural language …

From the last decade, Sentiment Analysis of languages such as English and Chinese are
particularly the focus of attention but resource poor languages such as Urdu are mostly …

Sentiment analysis aims to automatically classify the subject's sentiment (eg, positive,
negative, or neutral) towards a particular aspect such as a topic, product, movie, news, etc …

Sentiment Analysis (SA) is an application of Natural Language Processing (NLP) to extract
the sentiments expressed in the text. In this paper, we experimented five approaches to …

Most existing studies are focused on popular languages like English, Spanish, Chinese,
Japanese, and others, however, limited attention has been paid to Urdu despite having …