Nlp For Sentiment Analysis
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Nlp For Sentiment Analysis
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Author : Prof. Dr. Dileep Kumar M.
language : en
Publisher: Xoffencer International Book Publication
Release Date : 2024-10-25
Nlp For Sentiment Analysis written by Prof. Dr. Dileep Kumar M. and has been published by Xoffencer International Book Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-25 with Computers categories.
Natural Language Processing (NLP) has become a cornerstone in extracting and interpreting human emotions and opinions from text data, and one of its significant applications is sentiment analysis. Sentiment analysis aims to automatically identify subjective information within text, often categorizing sentiments as positive, negative, or neutral. This ability to quantify opinion and emotion has garnered interest from a broad range of industries—marketing, healthcare, finance, and customer service, to name a few—as organizations increasingly rely on insights derived from unstructured data like social media posts, reviews, and feedback forms. The rise in data-driven decision-making further underscores the importance of sentiment analysis, positioning it as a valuable tool in understanding public opinion, customer satisfaction, and user experience. With NLP, sentiment analysis transforms complex linguistic expressions into structured, analyzable data, enabling businesses and researchers to gauge public mood and predict behavior, thus facilitating more responsive and personalized services. Sentiment analysis is inherently challenging, however, as it requires deep comprehension of language structure, context, and the subtleties of human expression. Human language is diverse and laden with intricacies, including sarcasm, humor, regional dialects, and idiomatic expressions, which can complicate straightforward sentiment categorization. Modern sentiment analysis leverages a combination of machine learning, deep learning, and lexicon-based approaches to overcome these obstacles. Machine learning models like Support Vector Machines, Naive Bayes, and increasingly complex neural networks have been employed to classify sentiment, often with notable success. Deep learning, particularly through techniques such as Long Short-Term Memory (LSTM) networks and Transformer-based architectures like BERT and GPT, has further advanced sentiment analysis by enabling models to process long text sequences and capture contextual nuances. Lexicon-based approaches, on the other hand, involve predefined lists of words associated with sentiment, offering a more rule-based approach that can be useful in specific applications or as a complement to machine learning methods. In recent years, transfer learning has brought about substantial improvements in NLP for sentiment analysis, particularly through pretrained models that allow for fine-tuning on sentiment-specific tasks with minimal labeled data.
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
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
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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.
Advances In Sentiment Analysis
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Author :
language : en
Publisher: BoD – Books on Demand
Release Date : 2024-01-10
Advances In Sentiment Analysis written by and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-10 with Computers categories.
This cutting-edge book brings together experts in the field to provide a multidimensional perspective on sentiment analysis, covering both foundational and advanced methodologies. Readers will gain insights into the latest natural language processing and machine learning techniques that power sentiment analysis, enabling the extraction of nuanced emotions from text. Key Features: •State-of-the-Art Techniques: Explore the most recent advancements in sentiment analysis, from deep learning approaches to sentiment lexicons and beyond. •Real-World Applications: Dive into a wide range of applications, including social media monitoring, customer feedback analysis, and sentiment-driven decision-making. •Cross-Disciplinary Insights: Understand how sentiment analysis influences and is influenced by fields such as marketing, psychology, and finance. •Ethical and Privacy Considerations: Delve into the ethical challenges and privacy concerns inherent to sentiment analysis, with discussions on responsible AI usage. •Future Directions: Get a glimpse into the future of sentiment analysis, with discussions on emerging trends and unresolved challenges. This book is an essential resource for researchers, practitioners, and students in fields like natural language processing, machine learning, and data science. Whether you’re interested in understanding customer sentiment, monitoring social media trends, or advancing the state of the art, this book will equip you with the knowledge and tools you need to navigate the complex landscape of sentiment analysis.
Research Anthology On Implementing Sentiment Analysis Across Multiple Disciplines
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2022-06-10
Research Anthology On Implementing Sentiment Analysis Across Multiple Disciplines written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-10 with Computers categories.
The rise of internet and social media usage in the past couple of decades has presented a very useful tool for many different industries and fields to utilize. With much of the world’s population writing their opinions on various products and services in public online forums, industries can collect this data through various computational tools and methods. These tools and methods, however, are still being perfected in both collection and implementation. Sentiment analysis can be used for many different industries and for many different purposes, which could better business performance and even society. The Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines discusses the tools, methodologies, applications, and implementation of sentiment analysis across various disciplines and industries such as the pharmaceutical industry, government, and the tourism industry. It further presents emerging technologies and developments within the field of sentiment analysis and opinion mining. Covering topics such as electronic word of mouth (eWOM), public security, and user similarity, this major reference work is a comprehensive resource for computer scientists, IT professionals, AI scientists, business leaders and managers, marketers, advertising agencies, public administrators, government officials, university administrators, libraries, students and faculty of higher education, researchers, and academicians.
Advances In Natural Language Processing
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Author : Bengt Nordström
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-08-13
Advances In Natural Language Processing written by Bengt Nordström and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-13 with Computers categories.
This book constitutes the refereed proceedings of the 6th International Conference on Natural Language Processing, GoTAL 2008, Gothenburg, Sweden, August 2008. The 44 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 107 submissions. The papers address all current issues in computational linguistics and monolingual and multilingual intelligent language processing - theory, methods and applications.
Text Analytics With Python
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Author : Dipanjan Sarkar
language : en
Publisher: Apress
Release Date : 2019-05-21
Text Analytics With Python written by Dipanjan Sarkar and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-21 with Computers categories.
Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP. You’ll see how to use the latest state-of-the-art frameworks in NLP, coupled with machine learning and deep learning models for supervised sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move on to engineering representation methods for text data, including both traditional statistical models and newer deep learning-based embedding models. Improved techniques and new methods around parsing and processing text are discussed as well. Text summarization and topic models have been overhauled so the book showcases how to build, tune, and interpret topic models in the context of an interest dataset on NIPS conference papers. Additionally, the book covers text similarity techniques with a real-world example of movie recommenders, along with sentiment analysis using supervised and unsupervised techniques. There is also a chapter dedicated to semantic analysis where you’ll see how to build your own named entity recognition (NER) system from scratch. While the overall structure of the book remains the same, the entire code base, modules, and chapters has been updated to the latest Python 3.x release. What You'll Learn • Understand NLP and text syntax, semantics and structure• Discover text cleaning and feature engineering• Review text classification and text clustering • Assess text summarization and topic models• Study deep learning for NLP Who This Book Is For IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.
Sentiment Analysis Unveiled
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Author : Neha Nandal
language : en
Publisher: CRC Press
Release Date : 2025-04-02
Sentiment Analysis Unveiled written by Neha Nandal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-02 with Computers categories.
This book is a comprehensive exploration into the realm of sentiment analysis. From deciphering customer sentiments for businesses to understanding public opinions on social media or predicting market trends, the applications are multifaceted and impactful. Sentiment Analysis Unveiled: Techniques, Applications, and Innovations is more than just algorithms and models; it’s about unraveling the emotions, opinions, and perceptions encapsulated within the vast sea of textual data. This book explores topics from opinion mining, social media analysis, deep learning, security concerns, and healthcare systems, and it also delves into the ethical and legal implications of sentiment analysis. Through practical examples, case studies, and discussions on cutting‐edge innovations, the editors aim is to provide a holistic view that empowers you to navigate this field confidently. It involves the analysis of user‐generated content, deciphering sentiments expressed on platforms like Twitter and Facebook, and provides valuable insights into public opinion, brand perception, and emerging trends in the digital landscape. This book is intended for professionals, researchers, and scientists in the field of artificial intelligence and sentiments analysis; it will serve as a valuable resource for both beginners and experienced professionals in the field.
Natural Language Processing Practical Approach
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Author : Syed Muzamil Basha
language : en
Publisher: MileStone Research Publications
Release Date : 2023-02-26
Natural Language Processing Practical Approach written by Syed Muzamil Basha and has been published by MileStone Research Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-26 with Computers categories.
The "Natural Language Processing Practical Approach" is a textbook that provides a practical introduction to the field of Natural Language Processing (NLP). The goal of the textbook is to provide a hands-on, practical guide to NLP, with a focus on real-world applications and use cases. The textbook covers a range of NLP topics, including text preprocessing, sentiment analysis, named entity recognition, text classification, and more. The textbook emphasizes the use of algorithms and models to solve NLP problems and provides practical examples and code snippets in various programming languages, including Python. The textbook is designed for students, researchers, and practitioners in NLP who want to gain a deeper understanding of the field and build their own NLP projects. The current state of NLP is rapidly evolving with advancements in machine learning and deep learning techniques. The field has seen a significant increase in research and development efforts in recent years, leading to improved performance and new applications in areas such as sentiment analysis, text classification, language translation, and named entity recognition. The future prospects of NLP are bright, with continued development in areas such as reinforcement learning, transfer learning, and unsupervised learning, which are expected to further improve the performance of NLP models. Additionally, increasing amounts of text data available through the internet and growing demand for human-like conversational interfaces in areas such as customer service and virtual assistants will likely drive further advancements in NLP. The benefits of a hands-on, practical approach to natural language processing include: 1. Improved understanding: Practical approaches allow students to experience the concepts and techniques in action, helping them to better understand how NLP works. 2. Increased motivation: Hands-on approaches to learning can increase student engagement and motivation, making the learning process more enjoyable and effective. 3. Hands-on experience: By working with real data and implementing NLP techniques, students gain hands-on experience in applying NLP techniques to real-world problems. 4. Improved problem-solving skills: Practical approaches help students to develop problem-solving skills by working through real-world problems and challenges. 5. Better retention: When students have hands-on experience with NLP techniques, they are more likely to retain the information and be able to apply it in the future. A comprehensive understanding of NLP would include knowledge of its various tasks, techniques, algorithms, challenges, and applications. It also involves understanding the basics of computational linguistics, natural language understanding, and text representation methods such as tokenization, stemming, and lemmatization. Moreover, hands-on experience with NLP tools and libraries like NLTK, Spacy, and PyTorch would also enhance one's understanding of NLP.