Affective Computing And Sentiment Analysis
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Affective Computing And Sentiment Analysis
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Author : Khurshid Ahmad
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-24
Affective Computing And Sentiment Analysis written by Khurshid Ahmad 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 2011-08-24 with Computers categories.
This volume maps the watershed areas between two 'holy grails' of computer science: the identification and interpretation of affect – including sentiment and mood. The expression of sentiment and mood involves the use of metaphors, especially in emotive situations. Affect computing is rooted in hermeneutics, philosophy, political science and sociology, and is now a key area of research in computer science. The 24/7 news sites and blogs facilitate the expression and shaping of opinion locally and globally. Sentiment analysis, based on text and data mining, is being used in the looking at news and blogs for purposes as diverse as: brand management, film reviews, financial market analysis and prediction, homeland security. There are systems that learn how sentiments are articulated. This work draws on, and informs, research in fields as varied as artificial intelligence, especially reasoning and machine learning, corpus-based information extraction, linguistics, and psychology.
A Practical Guide To Sentiment Analysis
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Author : Erik Cambria
language : en
Publisher: Springer
Release Date : 2017-04-07
A Practical Guide To Sentiment Analysis written by Erik Cambria and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-07 with Medical categories.
Sentiment analysis research has been started long back and recently it is one of the demanding research topics. Research activities on Sentiment Analysis in natural language texts and other media are gaining ground with full swing. But, till date, no concise set of factors has been yet defined that really affects how writers’ sentiment i.e., broadly human sentiment is expressed, perceived, recognized, processed, and interpreted in natural languages. The existing reported solutions or the available systems are still far from perfect or fail to meet the satisfaction level of the end users. The reasons may be that there are dozens of conceptual rules that govern sentiment and even there are possibly unlimited clues that can convey these concepts from realization to practical implementation. Therefore, the main aim of this book is to provide a feasible research platform to our ambitious researchers towards developing the practical solutions that will be indeed beneficial for our society, business and future researches as well.
Sentic Computing
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Author : Erik Cambria
language : en
Publisher: Springer
Release Date : 2015-12-11
Sentic Computing written by Erik Cambria and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-11 with Medical categories.
This volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web. Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed: • Sentic Computing's multi-disciplinary approach to sentiment analysis-evidenced by the concomitant use of AI, linguistics and psychology for knowledge representation and inference • Sentic Computing’s shift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text • Sentic Computing's shift from statistics to linguistics-implemented by allowing sentiments to flow from concept to concept based on the dependency relation between clauses This volume is the first in the Series Socio-Affective Computing edited by Dr Amir Hussain and Dr Erik Cambria and will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction and systems.
Multimodal Sentiment Analysis
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Author : Soujanya Poria
language : en
Publisher:
Release Date : 2018
Multimodal Sentiment Analysis written by Soujanya Poria and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with COMPUTERS categories.
This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion. The inclusion of key visualization and case studies will enable readers to understand better these approaches.
Multimodal Sentiment Analysis
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Author : Soujanya Poria
language : en
Publisher: Springer
Release Date : 2018-10-24
Multimodal Sentiment Analysis written by Soujanya Poria and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-24 with Medical categories.
This latest volume in the series, Socio-Affective Computing, presents a set of novel approaches to analyze opinionated videos and to extract sentiments and emotions. Textual sentiment analysis framework as discussed in this book contains a novel way of doing sentiment analysis by merging linguistics with machine learning. Fusing textual information with audio and visual cues is found to be extremely useful which improves text, audio and visual based unimodal sentiment analyzer. This volume covers the three main topics of: textual preprocessing and sentiment analysis methods; frameworks to process audio and visual data; and methods of textual, audio and visual features fusion. The inclusion of key visualization and case studies will enable readers to understand better these approaches. Aimed at the Natural Language Processing, Affective Computing and Artificial Intelligence audiences, this comprehensive volume will appeal to a wide readership and will help readers to understand key details on multimodal sentiment analysis.
Sentiment Analysis In The Bio Medical Domain
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Author : Ranjan Satapathy
language : en
Publisher: Springer
Release Date : 2018-01-23
Sentiment Analysis In The Bio Medical Domain written by Ranjan Satapathy and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-23 with Medical categories.
The abundance of text available in social media and health-related forums and blogs have recently attracted the interest of the public health community to use these sources for opinion mining. This book presents a lexicon-based approach to sentiment analysis in the bio-medical domain, i.e., WordNet for Medical Events (WME). This book gives an insight in handling unstructured textual data and converting it to structured machine-processable data in the bio-medical domain. The readers will discover the following key novelties: 1) development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.; 2) ensemble of machine learning and computational creativity; 3) development of microtext analysis techniques to overcome the inconsistency in social communication. It will be of interest to researchers in the fields of socially-intelligent human-machine interaction and biomedical text mining
Multimodal Affective Computing Affective Information Representation Modelling And Analysis
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Author : Gyanendra K. Verma
language : en
Publisher: Bentham Science Publishers
Release Date : 2023-03-21
Multimodal Affective Computing Affective Information Representation Modelling And Analysis written by Gyanendra K. Verma and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Computers categories.
Computer Assistive Technologies for Physically and Cognitively Challenged Users focuses on the technologies and devices that assist individuals with physical and cognitive disabilities. These technologies facilitate independent activity and participation, serving to improve daily functional capabilities. The book features nine chapters that cover a wide range of computer assistive technologies that give readers an indepth understanding of the available resources to help the elderly or individuals with disabilities. The topics covered in the book include 1) The category and ontology of assistive devices, 2) Web accessibility and ICT accessibility for persons with disability (PWD), 3) Assistive technologies for blind and visually impaired people, 4) Assistive technologies for home comfort and care, 5) Assistive technologies for hearing impaired people using Indian sign language synthetic animations, 6) Augmentative and alternative communication/hearing impairments, 7) Accessibility innovations to help physically disabled users, 8) Adhesive tactile walking surface indicators for elderly and visually impaired people mobility, 9) future of assistive technologies This book serves as a textbook resource for students undertaking modular courses that require learning material on computer assistive technology. It also serves as a reference for graduate level courses in disability studies, humancomputer interaction, gerontology and rehabilitation engineering. Researchers working in the allied fields intersecting computer science, medicine and psychology will also benefit from the information provided in the book.
A Blueprint For Affective Computing
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Author : Klaus R. Scherer
language : en
Publisher: Oxford University Press
Release Date : 2010-09-23
A Blueprint For Affective Computing written by Klaus R. Scherer and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-23 with Computers categories.
'Affective computing' is a branch of computing concerned with the theory and construction of machines which can detect, respond to, and simulate human emotional states. This book presents an interdisciplinary exploration of this rapidly expanding field, aimed at those in psychology, computational neuroscience, computer science, and AI.
Applied Affective Computing
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Author : Leimin Tian
language : en
Publisher: Morgan & Claypool
Release Date : 2022-02-04
Applied Affective Computing written by Leimin Tian and has been published by Morgan & Claypool this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-04 with Computers categories.
Affective computing is a nascent field situated at the intersection of artificial intelligence with social and behavioral science. It studies how human emotions are perceived and expressed, which then informs the design of intelligent agents and systems that can either mimic this behavior to improve their intelligence or incorporate such knowledge to effectively understand and communicate with their human collaborators. Affective computing research has recently seen significant advances and is making a critical transformation from exploratory studies to real-world applications in the emerging research area known as applied affective computing. This book offers readers an overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches to affective computing systems and social signal processing. It provides in-depth case studies of applied affective computing in various domains, such as social robotics and mental well-being. It also addresses ethical concerns related to affective computing and how to prevent misuse of the technology in research and applications. Further, this book identifies future directions for the field and summarizes a set of guidelines for developing next-generation affective computing systems that are effective, safe, and human-centered. For researchers and practitioners new to affective computing, this book will serve as an introduction to the field to help them in identifying new research topics or developing novel applications. For more experienced researchers and practitioners, the discussions in this book provide guidance for adopting a human-centered design and development approach to advance affective computing.
Prominent Feature Extraction For Sentiment Analysis
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Author : Basant Agarwal
language : en
Publisher: Springer
Release Date : 2015-12-14
Prominent Feature Extraction For Sentiment Analysis written by Basant Agarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-14 with Medical categories.
The objective of this monograph is to improve the performance of the sentiment analysis model by incorporating the semantic, syntactic and common-sense knowledge. This book proposes a novel semantic concept extraction approach that uses dependency relations between words to extract the features from the text. Proposed approach combines the semantic and common-sense knowledge for the better understanding of the text. In addition, the book aims to extract prominent features from the unstructured text by eliminating the noisy, irrelevant and redundant features. Readers will also discover a proposed method for efficient dimensionality reduction to alleviate the data sparseness problem being faced by machine learning model. Authors pay attention to the four main findings of the book : -Performance of the sentiment analysis can be improved by reducing the redundancy among the features. Experimental results show that minimum Redundancy Maximum Relevance (mRMR) feature selection technique improves the performance of the sentiment analysis by eliminating the redundant features. - Boolean Multinomial Naive Bayes (BMNB) machine learning algorithm with mRMR feature selection technique performs better than Support Vector Machine (SVM) classifier for sentiment analysis. - The problem of data sparseness is alleviated by semantic clustering of features, which in turn improves the performance of the sentiment analysis. - Semantic relations among the words in the text have useful cues for sentiment analysis. Common-sense knowledge in form of ConceptNet ontology acquires knowledge, which provides a better understanding of the text that improves the performance of the sentiment analysis.