Deep learning-based approaches for sentiment analysis
This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field
1 online resource (326 pages)
9789811512162, 9789811512155, 9789811512179, 9789811512186, 9811512167, 9811512159, 9811512175, 9811512183
1138671925
Chapter 1. Application of Deep Learning Approaches for Sentiment Analysis: A Survey
Chapter 2. Recent Trends and Advances in Deep Learning based Sentiment Analysis
Chapter 3
Deep Learning Adaptation with Word Embeddings for Sentiment Analysis on Online Course Reviews
Chapter 4. Toxic Comment Detection in Online Discussions
Chapter 5. Aspect Based Sentiment Analysis of Financial Headlines and Microblogs
Chapter 6. Deep Learning based frameworks for Aspect Based Sentiment Analysis
Chapter 7. Transfer Learning for Detecting Hateful Sentiments in Code Switched Language
Chapter 8. Multilingual Sentiment Analysis
Chapter 9. Sarcasm Detection using deep learning
Chapter 10. Deep Learning Approaches for Speech Emotion Recognition
Chapter 11. Bidirectional Long Short Term Memory Based Spatio-Temporal In Community Question Answering
Chapter 12. Comparing Deep Neural Networks to Traditional Models for Sentiment Analysis in Turkish Language