Sentiment Analysis (Paperback)

Dr Arjun Kuruva

ISBN 10: 6209025587 / ISBN 13: 9786209025587

Published by LAP Lambert Academic Publishing, 2025

About this Item

Paperback. In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9786209025587

Bibliographic Details

• Title: Sentiment Analysis (Paperback)
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2025
• Language: English
• ISBN 10: 6209025587
• ISBN 13: 9786209025587
• Binding: Paperback
• Condition: new

About this title

Synopsis

In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing.