Sentiment Analysis Based on Deep Learning Approaches
Jaspreet Kaur, Brahmaleen Kaur Sidhu · 2018
Many emerging social sites, famous forums, review sites, and many bloggers generate huge amount of data in the form of user sentimental reviews, emotions, opinions, arguments, viewpoints etc. about different social events, products, brands, and politics, movies etc. Sentiments expressed by the users has great effect on readers, political images, online vendors. So the data present in scattered and unstructured manner needs to be managed properly and in this context sentiment analysis has got attention at very large level. Sentiment analysis can be defined as organization of the text which is used to understand the mind-sets or feelings expressed in the form of different manners such as negative, positive, neutral, not satisfactory etc. This paper explains the sentiment analysis, its levels and different approaches which are used with sentiment analysis.. Sentiment Analysis is one of the most popular application in text mining and with the integration of machine learning algorithms, deep learning algorithms it becomes more effective and is used in large number of businesses to increase their productivity and to make better customer experience. A review on how deep learning techniques are used by the researchers in different applications of sentiment analysis is also include in this paper. Sentiment analysis can be done using different techniques based on deep learning which is also elaborated in this paper. Thus this paper highlights latest studies regarding implementation of deep learning techniques for effective sentiment analysis.