Sanjiv Sharma – författare

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 detectionExplains the automatic detection and prevention of fake news and hate speech through paralinguistic clues on social media using artificial intelligenceDiscusses the application of machine learning models to learn linguistic characteristics of hate speech over social media platformsEmphasizes the role of multilingual and multimodal processing to detect fake newsIncludes research on different optimization techniques, case studies on the identification, prevention, and social impact of fake news, and GitHub repository links to aid understandingThe text is for professionals and scholars of various disciplines interested in fake news and hate speech detection.

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 detectionExplains the automatic detection and prevention of fake news and hate speech through paralinguistic clues on social media using artificial intelligenceDiscusses the application of machine learning models to learn linguistic characteristics of hate speech over social media platformsEmphasizes the role of multilingual and multimodal processing to detect fake newsIncludes research on different optimization techniques, case studies on the identification, prevention, and social impact of fake news, and GitHub repository links to aid understandingThe text is for professionals and scholars of various disciplines interested in fake news and hate speech detection.

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.

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.

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.

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.

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.

This case-based atlas encompasses all aspects of imaging in congenital cardiac defects, cardiac masses, inflammatory and acquired heart diseases, cardiomyopathies and coronary-related pathologies. The chapters begin with a description of the imaging approach, followed by cases comprehensively covering the gamut of clinical scenarios that may be encountered in clinical practice. The atlas provides pertinent information about each discussed disease state, its imaging diagnosis and recent advances, including role of radiology in management, follow up and prognostication. Cases that may pose as imaging differentials accompany the index case, followed by a variety of companion cases illustrating the possible spectrum of abnormalities that the reader may be confronted with while dealing with the index case. It acts as a guide for the cardiovascular radiologist, physician, paediatrician, internist, cardiologist, cardiothoracic surgeon as well as radiology residents for inculcating an evidence-based approach for choosing the right imaging algorithm in the given clinical situation. The highly visual design of the atlas enables it to act as a quick and ready reference.

This case-based atlas encompasses all aspects of imaging in congenital cardiac defects, cardiac masses, inflammatory and acquired heart diseases, cardiomyopathies and coronary-related pathologies. The chapters begin with a description of the imaging approach, followed by cases comprehensively covering the gamut of clinical scenarios that may be encountered in clinical practice. The atlas provides pertinent information about each discussed disease state, its imaging diagnosis and recent advances, including role of radiology in management, follow up and prognostication. Cases that may pose as imaging differentials accompany the index case, followed by a variety of companion cases illustrating the possible spectrum of abnormalities that the reader may be confronted with while dealing with the index case. It acts as a guide for the cardiovascular radiologist, physician, paediatrician, internist, cardiologist, cardiothoracic surgeon as well as radiology residents for inculcating an evidence-based approach for choosing the right imaging algorithm in the given clinical situation. The highly visual design of the atlas enables it to act as a quick and ready reference.