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 …

Sentiment analysis is a fundamental branch of natural language processing. It is an
essential task of identifying and extracting sentiment in opinionated data from sources such …

Nowadays the amount of textual information on the web is grown rapidly. The huge textual
data needs more accurate classification algorithms. Sentiment analysis is a branch of text …

Sentiment analysis has become a highly effective research field in the natural language
domain and has a large scope of real-world implementations. An existing active study …

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

Deep learning has made a great breakthrough in the field of speech and image recognition.
Mature deep learning neural network has completely changed the field of nat ural language …

Due to the enormous amount of data and opinions being produced, shared and transferred
everyday across the internet and other media, Sentiment analysis has become vital for …

Rapid growth of internet technology and social media is progressing. Data mining
technology has evolved to enable unstructured document representations in a variety of …

Analyzing the big textual information manually is tougher and time-consuming. Sentiment
analysis is a automated process that uses computing (AI) to spot positive and negative …