Big Data Analytics In Cognitive Social Media And Literary Texts
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Big Data Analytics in Cognitive Social Media and Literary Texts
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.
Social Media and Modern Society - How Social Media Are Changing the Way We Interact with the World Around
Author: Ján Višňovský
language: en
Publisher: BoD – Books on Demand
Release Date: 2024-11-27
This book offers a compelling exploration of how social media platforms are reshaping contemporary life, and driving economic, political, and cultural transformations. It brings together theoretical insights and empirical studies to examine the multifaceted impact of social media on communication, behavior, policy, and societal norms. The various chapters address critical issues such as digital marketing, social responsibility, and the role of influencers, emphasizing how businesses and individuals are navigating the evolving digital landscape. The book delves into pressing concerns, including the psychological effects of social media on youth, the spread of misinformation, and the challenges of digital addiction. It highlights the dual nature of social platforms as both enablers of civic engagement and sources of division, presenting case studies on topics such as political discourse, community activism, and local democracy.
Text and Social Media Analytics for 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.