Sentiment Analysis And Deep Learning
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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.
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.
Visual And Text Sentiment Analysis Through Hierarchical Deep Learning Networks
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Author : Arindam Chaudhuri
language : en
Publisher: Springer
Release Date : 2019-04-06
Visual And Text Sentiment Analysis Through Hierarchical Deep Learning Networks written by Arindam Chaudhuri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-06 with Computers categories.
This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis. The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book’s novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments; stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit; evaluation of HGFRNNs with different types of recurrent units; and adaptive assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.
Sentimental Analysis And Deep Learning
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Author : Subarna Shakya
language : en
Publisher: Springer Nature
Release Date : 2021-10-25
Sentimental 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 2021-10-25 with Technology & Engineering categories.
This book gathers selected papers presented at the International Conference on Sentimental Analysis and Deep Learning (ICSADL 2021), jointly organized by Tribhuvan University, Nepal; Prince of Songkla University, Thailand; and Ejesra during June, 18–19, 2021. 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. Meanwhile, deep learning emerges as the revolutionary paradigm with its extensive data-driven representation learning architectures. This book discusses all theoretical aspects of sentimental analysis, deep learning and related topics.
New Opportunities For Sentiment Analysis And Information Processing
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Author : Sharaff, Aakanksha
language : en
Publisher: IGI Global
Release Date : 2021-06-25
New Opportunities For Sentiment Analysis And Information Processing written by Sharaff, Aakanksha and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Computers categories.
Multinational organizations have begun to realize that sentiment mining plays an important role for decision making and market strategy. The revolutionary growth of digital marketing not only changes the market game, but also brings forth new opportunities for skilled professionals and expertise. Currently, the technologies are rapidly changing, and artificial intelligence (AI) and machine learning are contributing as game-changing technologies. These are not only trending but are also increasingly popular among data scientists and data analysts. New Opportunities for Sentiment Analysis and Information Processing provides interdisciplinary research in information retrieval and sentiment analysis including studies on extracting sentiments from textual data, sentiment visualization-based dimensionality reduction for multiple features, and deep learning-based multi-domain sentiment extraction. The book also optimizes techniques used for sentiment identification and examines applications of sentiment analysis and emotion detection. Covering such topics as communication networks, natural language processing, and semantic analysis, this book is essential for data scientists, data analysts, IT specialists, scientists, researchers, academicians, and students.
Comparison Of Neutrosophic Approach To Various Deep Learning Models For Sentiment Analysis
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Author : Mayukh Sharma
language : en
Publisher: Infinite Study
Release Date :
Comparison Of Neutrosophic Approach To Various Deep Learning Models For Sentiment Analysis written by Mayukh Sharma and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
Deep learning has been widely used in numerous real-world engineering applications and for classification problems. Real-world data is present with neutrality and indeterminacy, which neutrosophic theory captures clearly. Though both are currently developing research areas, there has been little study on their interlinking. We have proposed a novel framework to implement neutrosophy in deep learning models. Instead of just predicting a single class as output, we have quantified the sentiments using three membership functions to understand them better. Our proposed model consists of two blocks, feature extraction, and feature classification.
Deep Learning Based Approaches For Sentiment Analysis
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Author :
language : en
Publisher:
Release Date : 2020
Deep Learning Based Approaches For Sentiment Analysis written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Data mining 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 Its Application In Educational Data Mining
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Author : Soni Sweta
language : en
Publisher: Springer Nature
Release Date :
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 with categories.
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 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.