Sentimental Analysis and Deep Learning : A Survey

Sentiment Analysis is an ongoing field of research in text mining. Sentiment Analysis is the computational treatment of opinions, Sentiments, and subjectivity of text. Many recently proposed algorithms enhancements and various Sentiment Analysis applications are investigated and presented briefly in this survey. The related fields to Sentiment Analysis that attracted researchers recently are discussed. The main target of this survey is to give nearly full image of Sentiment Analysis techniques and the related fields with brief details. In recent years machine learning has received greater attention with the success of deep learning. Deep learning can create deep models of complex multivariate structures in structured data. Though deep learning can be characterized in several different ways, the most important is that deep learning can learn higher-order interactions among features using a cascade of many layers. Deep learning has been applied to neural networks and across many fields, with significant successes in many applications. Convolution neural networks, deep belief networks, and many other approaches have been proposed to enhance the abilities of deep structure networks