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4 books on Sentiment Analysis [PDF]
Updated: March 22, 2024 | 29 |
Books on Sentiment Analysis offer a wealth of knowledge for startups specializing in the development of sentiment analysis solutions. These resources provide a comprehensive foundation, covering various aspects of natural language processing, machine learning, and text analysis techniques used in sentiment analysis. They delve into the complexities of understanding and classifying human emotions and opinions expressed in text data, emphasizing the importance of accuracy and context. Moreover, these books often include practical examples, sentiment lexicons, and real-world use cases, enabling startups to learn from successful sentiment analysis implementations.
1. New Opportunities for Sentiment Analysis and Information Processing
2021 by Sharaff, Aakanksha, Sinha, G. R., Bhatia, Surbhi
"New Opportunities for Sentiment Analysis and Information Processing" presents a cross-disciplinary exploration of information retrieval and sentiment analysis, encompassing research on extracting sentiments from text data, reducing dimensionality through sentiment visualization, and implementing deep learning for multi-domain sentiment extraction. The book also refines sentiment identification techniques and explores the practical applications of sentiment analysis and emotion detection. Addressing communication networks, natural language processing, and semantic analysis, this volume serves as a vital resource for data scientists, IT professionals, researchers, academics, students, and data analysts."
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2. Sentiment Analysis: Mining Opinions, Sentiments, and Emotions
2020 by Bing Liu
"Sentiment analysis, also known as the computational examination of people's opinions, sentiments, emotions, moods, and attitudes, represents an intriguing field of study. This captivating subject poses numerous research challenges while holding the potential to provide valuable insights for those interested in opinion and social media analysis. This comprehensive guide, taking a natural language processing approach, aims to elucidate the underlying structure of sentiment analysis and the common linguistic elements used to express opinions, sentiments, and emotions. It not only delves into the fundamental aspects of sentiment analysis but also explores related topics such as debate analysis, intention mining, and fake-opinion detection. Targeting researchers and practitioners in various fields, including natural language processing, computer science, management sciences, and social sciences, this second edition extends its coverage to encompass recent deep learning techniques for sentiment and opinion analysis, as well as new content on emotion and mood analysis methods, emotion-enhanced dialogues, and multimodal emotion analysis."
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3. Multimodal Sentiment Analysis
2018 by Soujanya Poria, Amir Hussain, Erik Cambria
"This recent addition to the Socio-Affective Computing series introduces innovative techniques for the analysis of opinionated videos and the extraction of sentiments and emotions. The book introduces a novel approach to sentiment analysis that blends linguistics and machine learning, enhancing unimodal sentiment analysis based on text, audio, and visual cues. It encompasses three key areas: textual preprocessing and sentiment analysis methods, frameworks for audio and visual data processing, and techniques for fusing textual, audio, and visual features. The volume incorporates essential visualizations and case studies to facilitate a deeper understanding of these methods. With a target audience spanning Natural Language Processing, Affective Computing, and Artificial Intelligence, this comprehensive book will benefit a broad readership, providing valuable insights into multimodal sentiment analysis."
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4. Semantic Sentiment Analysis in Social Streams
2017 by H. Saif
"In this book, Twitter serves as a compelling case study for exploring the enhancement of sentiment analysis by considering the semantic aspects of words. The author investigates the incorporation of two types of word semantics, namely contextual semantics (derived from co-occurrences) and conceptual semantics (extracted from external knowledge sources), into sentiment analysis models. Through a series of experiments spanning three common sentiment analysis tasks on Twitter—entity-level sentiment analysis, tweet-level sentiment analysis, and context-sensitive sentiment lexicon adaptation—the book highlights the significant impact of semantics on sentiment analysis accuracy. The proposed semantic approaches, tailored for both entities and tweets, outperform non-semantic methods in various evaluation scenarios. This book is a valuable resource for students, researchers, and practitioners in the field of semantic sentiment analysis."
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. New Opportunities for Sentiment Analysis and Information Processing
2021 by Sharaff, Aakanksha, Sinha, G. R., Bhatia, Surbhi
"New Opportunities for Sentiment Analysis and Information Processing" presents a cross-disciplinary exploration of information retrieval and sentiment analysis, encompassing research on extracting sentiments from text data, reducing dimensionality through sentiment visualization, and implementing deep learning for multi-domain sentiment extraction. The book also refines sentiment identification techniques and explores the practical applications of sentiment analysis and emotion detection. Addressing communication networks, natural language processing, and semantic analysis, this volume serves as a vital resource for data scientists, IT professionals, researchers, academics, students, and data analysts."
Download PDF
2. Sentiment Analysis: Mining Opinions, Sentiments, and Emotions
2020 by Bing Liu
"Sentiment analysis, also known as the computational examination of people's opinions, sentiments, emotions, moods, and attitudes, represents an intriguing field of study. This captivating subject poses numerous research challenges while holding the potential to provide valuable insights for those interested in opinion and social media analysis. This comprehensive guide, taking a natural language processing approach, aims to elucidate the underlying structure of sentiment analysis and the common linguistic elements used to express opinions, sentiments, and emotions. It not only delves into the fundamental aspects of sentiment analysis but also explores related topics such as debate analysis, intention mining, and fake-opinion detection. Targeting researchers and practitioners in various fields, including natural language processing, computer science, management sciences, and social sciences, this second edition extends its coverage to encompass recent deep learning techniques for sentiment and opinion analysis, as well as new content on emotion and mood analysis methods, emotion-enhanced dialogues, and multimodal emotion analysis."
Download PDF
3. Multimodal Sentiment Analysis
2018 by Soujanya Poria, Amir Hussain, Erik Cambria
"This recent addition to the Socio-Affective Computing series introduces innovative techniques for the analysis of opinionated videos and the extraction of sentiments and emotions. The book introduces a novel approach to sentiment analysis that blends linguistics and machine learning, enhancing unimodal sentiment analysis based on text, audio, and visual cues. It encompasses three key areas: textual preprocessing and sentiment analysis methods, frameworks for audio and visual data processing, and techniques for fusing textual, audio, and visual features. The volume incorporates essential visualizations and case studies to facilitate a deeper understanding of these methods. With a target audience spanning Natural Language Processing, Affective Computing, and Artificial Intelligence, this comprehensive book will benefit a broad readership, providing valuable insights into multimodal sentiment analysis."
Download PDF
4. Semantic Sentiment Analysis in Social Streams
2017 by H. Saif
"In this book, Twitter serves as a compelling case study for exploring the enhancement of sentiment analysis by considering the semantic aspects of words. The author investigates the incorporation of two types of word semantics, namely contextual semantics (derived from co-occurrences) and conceptual semantics (extracted from external knowledge sources), into sentiment analysis models. Through a series of experiments spanning three common sentiment analysis tasks on Twitter—entity-level sentiment analysis, tweet-level sentiment analysis, and context-sensitive sentiment lexicon adaptation—the book highlights the significant impact of semantics on sentiment analysis accuracy. The proposed semantic approaches, tailored for both entities and tweets, outperform non-semantic methods in various evaluation scenarios. This book is a valuable resource for students, researchers, and practitioners in the field of semantic sentiment analysis."
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
