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.
Sentiment Analysis With Machine Learning A Project Based Guide
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Author : Ashish Rajaram Lahase
language : en
Publisher: IIP Iterative International Publishers
Release Date : 2025-04-26
Sentiment Analysis With Machine Learning A Project Based Guide written by Ashish Rajaram Lahase and has been published by IIP Iterative International Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-26 with Computers categories.
In the beginning, we embark on a journey that invites reflection and contemplation. This introduction serves as a gateway to the ideas and themes that will unfold in the pages that follow. It is a moment to set the stage, to provide context, and to share the intentions behind this work. As we delve into the narrative, may the insights and experiences resonate deeply, guiding the reader through the exploration ahead. In recent years, the exploration of sentiment analysis has taken on significant importance within the realm of Natural Language Processing (NLP). This burgeoning field empowers businesses, researchers, and individuals alike to glean meaningful insights from the vast expanse of textual data. In an age where the proliferation of user-generated content on social media, product reviews, and online discussions is unprecedented, the comprehension of sentiments emerges as a crucial element for informed decision-making across diverse fields. This work, Sentiment Analysis with Machine Learning: A Project-Based Guide, aims to offer a thorough and pragmatic pathway for understanding and applying sentiment analysis techniques. This work has been thoughtfully organized to function as a practical resource, intertwining foundational theories with tangible applications in the real world. Our foremost intention is to guide readers in grasping the essential principles of sentiment analysis while simultaneously providing them with the opportunity to acquire hands-on experience through engaging in projects that utilize a range of machine learning techniques. In the following pages, we embark on a journey through essential themes, delving into the intricacies of text preprocessing, the art of feature engineering, the distinctions between supervised and unsupervised learning methods, the critical evaluation of sentiment analysis models. In this work, we present a selection of thoughtfully chosen project-based examples, designed to empower readers to translate their understanding into practical applications within real-world contexts. This work presents a meticulously organized, sequential methodology designed to serve the needs of students, researchers, and professionals aspiring to cultivate their proficiency in sentiment analysis. We wish to express our heartfelt appreciation to all those who have contributed to the creation of this work. From our esteemed mentors and dedicated colleagues to the vibrant research community that tirelessly propels this captivating field forward, your support has been invaluable. This work aspires to be a significant resource for individuals keen to delve into the possibilities of sentiment analysis within the dynamic realms of artificial intelligence and data science.
Sentiment Analysis Using Deep Learning
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Author : Miao Wei
language : en
Publisher:
Release Date : 2017
Sentiment Analysis Using Deep Learning written by Miao Wei and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Computer Science Theses categories.
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.
Deep Learning For Social Media Data Analytics
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Author : Tzung-Pei Hong
language : en
Publisher: Springer Nature
Release Date : 2022-09-18
Deep Learning For Social Media Data Analytics written by Tzung-Pei Hong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-18 with Computers categories.
This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics.
Deep Learning Approach To Sentiment Analysis In Health And Well Being
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Author : Anastazia Zunic
language : en
Publisher:
Release Date : 2022
Deep Learning Approach To Sentiment Analysis In Health And Well Being written by Anastazia Zunic and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
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.