Deep Learning Approaches and Security Domains in Sentiment Analysis

Sentiment recognition from voice signal is an important but challenging element of human machine interaction. In the state of art many machine learning techniques have been utilized to recognize the emotions from text sources available in social media. Recently, deep learning techniques has become an alternative to recognize emotions from speech signal. This paper explores the power of deep learning techniques, highlighting their success across diverse fields like e-commerce, business planning, mental health evaluation, image and speech recognition, natural language processing, and more. It provides a comprehensive review of popular deep learning methods, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, and Deep Belief Networks (DBNs). Additionally, the paper compares and contrasts traditional machine learning approaches with deep learning methods. Different security domains and issues in social media w.r.t social media users, their information are covered in this paper.