Description
Approx.330 pagesApprox.330 pages
Table of Contents
1. Introduction to Text and Sentiment Data Analysis2. Natural Language Processing and Sentiment Analysis: Perspectives from Computational Intelligence3. Applications and Challenges of Sentiment Analysis in Real Life Scenarios4. Emotions Recognition of Students from Online and Offline Texts5. Online Social Network Sensing Models6. Identifying Sentiments of Hate Speech using Deep Learning7. An Annotation System to Summarize Medical Corpus using Sentiment based Models8. Deep learning-based Dataset Recommendation System by employing Emotions9. Hybrid Deep Learning Architecture Performance on Large English Sentiment Text Data: Merits and Challenges10. Human-centered Sentiment Analysis11. An Interactive Tutoring System for Older Adults - Learning with New Apps12. Irony and Sarcasm Detection13. Concluding Remarks
