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Author: Sanjiv Sharma
Publisher: Springer Nature
ISBN: 9811647291
Category : Language Arts & Disciplines
Languages : en
Pages : 316
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Book Description
This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media & communication studies and computational/digital humanities.
Author: Sanjiv Sharma
Publisher: Springer Nature
ISBN: 9811647291
Category : Language Arts & Disciplines
Languages : en
Pages : 316
Get Book Here
Book Description
This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media & communication studies and computational/digital humanities.
Author: Hemant Kumar Soni
Publisher: CRC Press
ISBN: 104010049X
Category : Computers
Languages : en
Pages : 325
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Book Description
Identifying and stopping the dissemination of fabricated news, hate speech, or deceptive information camouflaged as legitimate news poses a significant technological hurdle. This book presents emergent methodologies and technological approaches of natural language processing through machine learning for counteracting the spread of fake news and hate speech on social media platforms. • Covers various approaches, algorithms, and methodologies for fake news and hate speech detection. • Explains the automatic detection and prevention of fake news and hate speech through paralinguistic clues on social media using artificial intelligence. • Discusses the application of machine learning models to learn linguistic characteristics of hate speech over social media platforms. • Emphasizes the role of multilingual and multimodal processing to detect fake news. • Includes research on different optimization techniques, case studies on the identification, prevention, and social impact of fake news, and GitHub repository links to aid understanding. The text is for professionals and scholars of various disciplines interested in fake news and hate speech detection.
Author: Rosário, Albérico Travassos
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 454
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Book Description
In the field of modern marketing, a pivotal challenge emerges as traditional strategies grapple with the complexities of an increasingly data-centric world. Marketers, researchers, and business consultants find themselves at a crossroads, navigating the intricate intersection of data science and strategic marketing practices. This challenge serves as the catalyst for Data-Driven Marketing for Strategic Success, a guide designed to address the pressing issues faced by academic scholars and professionals alike. This comprehensive exploration unveils the transformative power of data in reshaping marketing strategies, offering a beacon of strategic success in a sea of uncertainty. This book transcends the realm of traditional marketing literature. It stands as a useful resource, not merely adding elements to ongoing research but shaping the very future of how researchers, practitioners, and students engage with the dynamic world of data-driven marketing. It is strategically tailored to reach a diverse audience, offering valuable insights to academics and researchers exploring advanced topics, practitioners in the marketing industry seeking practical applications, and graduate students studying data science, marketing, and business analytics. Policymakers, ethicists, and industry regulators will find the dedicated section on ethical considerations particularly relevant, emphasizing the importance of responsible practices in the data-driven marketing landscape.
Author: Shalin Hai-Jew
Publisher: Springer
ISBN: 3319544993
Category : Computers
Languages : en
Pages : 304
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Book Description
This book covers computationally innovative methods and technologies including data collection and elicitation, data processing, data analysis, data visualizations, and data presentation. It explores how digital humanists have harnessed the hypersociality and social technologies, benefited from the open-source sharing not only of data but of code, and made technological capabilities a critical part of humanities work. Chapters are written by researchers from around the world, bringing perspectives from diverse fields and subject areas. The respective authors describe their work, their research, and their learning. Topics include semantic web for cultural heritage valorization, machine learning for parody detection by classification, psychological text analysis, crowdsourcing imagery coding in natural disasters, and creating inheritable digital codebooks.Designed for researchers and academics, this book is suitable for those interested in methodologies and analytics that can be applied in literature, history, philosophy, linguistics, and related disciplines. Professionals such as librarians, archivists, and historians will also find the content informative and instructive.
Author: Faisal Saeed
Publisher: Springer Nature
ISBN: 3031597079
Category :
Languages : en
Pages : 332
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Book Description
Author: Keikhosrokiani, Pantea
Publisher: IGI Global
ISBN: 1799895963
Category : Computers
Languages : en
Pages : 462
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Book Description
Opinion mining and text analytics are used widely across numerous disciplines and fields in today’s society to provide insight into people’s thoughts, feelings, and stances. This data is incredibly valuable and can be utilized for a range of purposes. As such, an in-depth look into how opinion mining and text analytics correlate with social media and literature is necessary to better understand audiences. The Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media introduces the use of artificial intelligence and big data analytics applied to opinion mining and text analytics on literary works and social media. It also focuses on theories, methods, and approaches in which data analysis techniques can be used to analyze data to provide a meaningful pattern. Covering a wide range of topics such as sentiment analysis and stance detection, this publication is ideal for lecturers, researchers, academicians, practitioners, and students.
Author: Keikhosrokiani, Pantea
Publisher: IGI Global
ISBN: 1668470314
Category : Computers
Languages : en
Pages : 428
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Book Description
Although there are various studies on theories and analytical techniques to address consumer behavior change in the current world, tracking consumer behavior change in the metaverse and the adoption of the metaverse remains a challenge that requires discussion. The advent of the metaverse will have a profound influence on consumer behavior, from how people make decisions and create brand connections to how they feel about their avatar embodiment and their purchases in the metaverse. The Handbook of Research on Consumer Behavioral Analytics in Metaverse and the Adoption of a Virtual World investigates the social, behavioral, and psychological factors that influence metaverse adoption. The focus then shifts to concepts, theories, and analytical approaches for detecting changes in consumer behavior in the metaverse. Covering topics such as e-commerce markets, user experience, and immersive technologies, this major reference work is an excellent resource for business executives, entrepreneurs, data analysts, marketers, advertisers, government officials, social media professionals, librarians, students and educators of higher education, researchers, and academicians.
Author: Macnish Kevin Macnish
Publisher: Edinburgh University Press
ISBN: 147446355X
Category : Philosophy
Languages : en
Pages : 256
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Book Description
What's wrong with targeted advertising in political campaigns? Should we be worried about echo chambers? How does data collection impact on trust in society? As decision-making becomes increasingly automated, how can decision-makers be held to account? This collection consider potential solutions to these challenges. It brings together original research on the philosophy of big data and democracy from leading international authors, with recent examples - including the 2016 Brexit Referendum, the Leveson Inquiry and the Edward Snowden leaks. And it asks whether an ethical compass is available or even feasible in an ever more digitised and monitored world.
Author: Dr. Alfio Gliozzo
Publisher: IBM Redbooks
ISBN: 073844264X
Category : Computers
Languages : en
Pages : 130
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Book Description
The Building Cognitive Applications with IBM Watson Services series is a seven-volume collection that introduces IBM® WatsonTM cognitive computing services. The series includes an overview of specific IBM Watson® services with their associated architectures and simple code examples. Each volume describes how you can use and implement these services in your applications through practical use cases. The series includes the following volumes: Volume 1 Getting Started, SG24-8387 Volume 2 Conversation, SG24-8394 Volume 3 Visual Recognition, SG24-8393 Volume 4 Natural Language Classifier, SG24-8391 Volume 5 Language Translator, SG24-8392 Volume 6 Speech to Text and Text to Speech, SG24-8388 Volume 7 Natural Language Understanding, SG24-8398 Whether you are a beginner or an experienced developer, this collection provides the information you need to start your research on Watson services. If your goal is to become more familiar with Watson in relation to your current environment, or if you are evaluating cognitive computing, this collection can serve as a powerful learning tool. This IBM Redbooks® publication, Volume 1, introduces cognitive computing, its motivating factors, history, and basic concepts. This volume describes the industry landscape for cognitive computing and introduces Watson, the cognitive computing offering from IBM. It also describes the nature of the question-answering (QA) challenge that is represented by the Jeopardy! quiz game and it provides a high-level overview of the QA system architecture (DeepQA), developed for Watson to play the game. This volume charts the evolution of the Watson Developer Cloud, from the initial DeepQA implementation. This book also introduces the concept of domain adaptation and the processes that must be followed to adapt the various Watson services to specific domains.
Author: Peter Ghavami
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 1547401567
Category : Business & Economics
Languages : en
Pages : 254
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Book Description
Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.
