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Deep Learning Approaches for Textual Sentiment Analysis
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Author(s): Tamanna Sharma (Department of Computer Science and Technology, Guru Jambheshwar University of Science and Technology, Hisar, India), Anu Bajaj (Department of Computer Science and Engineering, Guru Jambheshwar University of Science and Technology, Hisar, India)and Om Prakash Sangwan (Department of Computer Science and Technology, Guru Jambheshwar University of Science and Technology, Hisar, India)
Copyright: 2022
Pages: 12
Source title:
Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6303-1.ch014
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Abstract
Sentiment analysis is computational measurement of attitude, opinions, and emotions (like positive/negative) with the help of text mining and natural language processing of words and phrases. Incorporation of machine learning techniques with natural language processing helps in analysing and predicting the sentiments in more precise manner. But sometimes, machine learning techniques are incapable in predicting sentiments due to unavailability of labelled data. To overcome this problem, an advanced computational technique called deep learning comes into play. This chapter highlights latest studies regarding use of deep learning techniques like convolutional neural network, recurrent neural network, etc. in sentiment analysis.
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