Sentiment Analysis
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Sentiment Analysis
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Author : Bing Liu
language : en
Publisher: Cambridge University Press
Release Date : 2020-10-15
Sentiment Analysis written by Bing Liu and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-15 with Business & Economics categories.
A comprehensive introduction to computational analysis of sentiments, opinions, emotions, and moods. Now including deep learning methods.
Sentiment Analysis And Opinion Mining
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Author : Bing Liu
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2012-05-01
Sentiment Analysis And Opinion Mining written by Bing Liu and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-01 with Computers categories.
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography
Sentiment Analysis And Opinion Mining
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Author : Bing Liu
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Sentiment Analysis And Opinion Mining written by Bing Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography
Sentiment Analysis And Its Application In Educational Data Mining
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Author : Soni Sweta
language : en
Publisher: Springer Nature
Release Date : 2024-04-20
Sentiment Analysis And Its Application In Educational Data Mining written by Soni Sweta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-20 with Computers categories.
The book delves into the fundamental concepts of sentiment analysis, its techniques, and its practical applications in the context of educational data. The book begins by introducing the concept of sentiment analysis and its relevance in educational settings. It provides a thorough overview of the various techniques used for sentiment analysis, including natural language processing, machine learning, and deep learning algorithms. The subsequent chapters explore applications of sentiment analysis in educational data mining across multiple domains. The book illustrates how sentiment analysis can be employed to analyze student feedback and sentiment patterns, enabling educators to gain valuable insights into student engagement, motivation, and satisfaction. It also examines how sentiment analysis can be used to identify and address students' emotional states, such as stress, boredom, or confusion, leading to more personalized and effective interventions. Furthermore, the book explores the integration of sentiment analysis with other educational data mining techniques, such as clustering, classification, and predictive modeling. It showcases real-world case studies and examples that demonstrate how sentiment analysis can be combined with these approaches to improve educational decision-making, curriculum design, and adaptive learning systems.
Sentiment Analysis And Deep Learning
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Author : Subarna Shakya
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Sentiment Analysis And Deep Learning written by Subarna Shakya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Technology & Engineering categories.
This book gathers selected papers presented at International Conference on Sentimental Analysis and Deep Learning (ICSADL 2022), jointly organized by Tribhuvan University, Nepal and Prince of Songkla University, Thailand during 16 – 17 June, 2022. The volume discusses state-of-the-art research works on incorporating artificial intelligence models like deep learning techniques for intelligent sentiment analysis applications. Emotions and sentiments are emerging as the most important human factors to understand the prominent user-generated semantics and perceptions from the humongous volume of user-generated data. In this scenario, sentiment analysis emerges as a significant breakthrough technology, which can automatically analyze the human emotions in the data-driven applications. Sentiment analysis gains the ability to sense the existing voluminous unstructured data and delivers a real-time analysis to efficiently automate the business processes.
Sentiment Analysis For Social Media
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Author : Carlos A. Iglesias
language : en
Publisher: MDPI
Release Date : 2020-04-02
Sentiment Analysis For Social Media written by Carlos A. Iglesias and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-02 with Technology & Engineering categories.
Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection.
Sentiment Analysis In Social Networks
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Author : Federico Alberto Pozzi
language : en
Publisher: Morgan Kaufmann
Release Date : 2016-10-06
Sentiment Analysis In Social Networks written by Federico Alberto Pozzi and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-06 with Computers categories.
The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network analysis - Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network mining - Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics
Deep Learning Based Approaches For Sentiment Analysis
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Author : Basant Agarwal
language : en
Publisher: Springer Nature
Release Date : 2020-01-24
Deep Learning Based Approaches For Sentiment Analysis written by Basant Agarwal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-24 with Technology & Engineering categories.
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.
Sentiment Analysis And Knowledge Discovery In Contemporary Business
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Author : Rajput, Dharmendra Singh
language : en
Publisher: IGI Global
Release Date : 2018-08-31
Sentiment Analysis And Knowledge Discovery In Contemporary Business written by Rajput, Dharmendra Singh and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-31 with Business & Economics categories.
In the era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through online collaborative media. However, conducting sentiment analysis on these platforms can be challenging, especially for business professionals who are using them to collect vital data. Sentiment Analysis and Knowledge Discovery in Contemporary Business is an essential reference source that discusses applications of sentiment analysis as well as data mining, machine learning algorithms, and big data streams in business environments. Featuring research on topics such as knowledge retrieval and knowledge updating, this book is ideally designed for business managers, academicians, business professionals, researchers, graduate-level students, and technology developers seeking current research on data collection and management to drive profit.
Computational Intelligence Methods For Sentiment Analysis In Natural Language Processing Applications
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Author : D. Jude Hemanth
language : en
Publisher: Elsevier
Release Date : 2024-01-19
Computational Intelligence Methods For Sentiment Analysis In Natural Language Processing Applications written by D. Jude Hemanth and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-19 with Computers categories.
Sentiment Analysis has become increasingly important in recent years for nearly all online applications. Sentiment Analysis depends heavily on Artificial Intelligence (AI) technology wherein computational intelligence approaches aid in deriving the opinions/emotions of human beings. With the vast increase in Big Data, computational intelligence approaches have become a necessity for Natural Language Processing and Sentiment Analysis in a wide range of decision-making application areas. The applications of Sentiment Analysis are enormous, ranging from business to biomedical and clinical applications. However, the combination of AI methods and Sentiment Analysis is one of the rarest commodities in the literature. The literatures either gives more importance to the application alone or to the AI/CI methodology.Computational Intelligence for Sentiment Analysis in Natural Language Processing Applications provides a solution to this problem through detailed technical coverage of AI-based Sentiment Analysis methods for various applications. The authors provide readers with an in-depth look at the challenges and solutions associated with the different types of Sentiment Analysis, including case studies and real-world scenarios from across the globe. Development of scientific and enterprise applications are covered, which will aid computer scientists in building practical/real-world AI-based Sentiment Analysis systems. - Includes basic concepts, technical explanations, and case studies for in-depth explanation of the Sentiment Analysis - Aids computer scientists in developing practical/real-world AI-based Sentiment Analysis systems - Provides readers with real-world development applications of AI-based Sentiment Analysis, including transfer learning for opinion mining from pandemic medical data, sarcasm detection using neural networks in human-computer interaction, and emotion detection using the random-forest algorithm