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 is an accessible introduction to the study of detecting fake news on social media. The concepts, algorithms, and methods described in this book can help harness the power of social media to build effective and intelligent fake news detection systems. In the past decade, social media is becoming increasingly popular for news consumption due to its easy access, fast dissemination, and low cost. However, social media also enables the wide propagation of "fake news," i.e., news with intentionally false information. Fake news on social media can have significant negative societal effects. Therefore, fake news detection on social media has recently become an emerging research that is attracting tremendous attention. From a data mining perspective, this book introduces the basic concepts and characteristics of fake news across disciplines, reviews representative fake news detection methods in a principled way, and illustrates advanced settings of fake news detection on social media. In particular, the authors discuss the value of news content and social context, as well as important extensions to handle early detection, weakly-supervised detection, and explainable detection. This is essential reading for students, researchers, and practitioners to understand, manage, and excel in this area. This book is supported by additional materials, including lecture slides, the complete set of figures, key references, datasets, tools used in this book, and the source code of representative algorithms.

This reference text presents the important components for grasping the potential of social computing with an emphasis on concerns, challenges, and benefits of the social platform in depth. Features: Detailed discussion on social-cyber issues, including hate speech, cyberbullying, and others Discusses usefulness of social platforms for societal needs Includes framework to address the social issues with their implementations Covers fake news and rumor detection models Describes sentimental analysis of social posts with advanced learning techniques The book is ideal for undergraduate, postgraduate, and research students who want to learn about the issues, challenges, and solutions of social platforms in depth.

This book presents the papers included in the proceedings of the 3rd International Conference of Advanced Computing and Informatics (ICACin’22) that was held in Casablanca, Morocco, on October 15–16, 2022. A total of 98 papers were submitted to the conference, but only 60 papers were accepted and published in this book with an acceptance rate of 61%. The book presents several hot research topics which include artificial intelligence and data science, big data analytics, Internet of Things (IoT) and smart cities, information security, cloud computing and networking, and computational informatics.

This book constitutes selected and revised papers from the First International Workshop on Combating On​line Ho​st​ile Posts in ​Regional Languages dur​ing Emerge​ncy Si​tuation, CONSTRAINT 2021, Collocated with AAAI 2021, held as virtual event, in February 2021. The 14 full papers and 9 short papers presented were thoroughly reviewed and selected from 62 qualified submissions. The papers present interdisciplinary approaches on multilingual social media analytics and non-conventional ways of combating online hostile posts.

The book presents high-quality research papers presented at the International Conference on Computational Intelligence and Data Analytics (ICCIDA 2022), organized by the Department of Information Technology, Vasavi College of Engineering, Hyderabad, India in January 2022. ICCIDA provides an excellent platform for exchanging knowledge with the global community of scientists, engineers, and educators. This volume covers cutting-edge research in two prominent areas – computational intelligence and data analytics, and allied research areas.

This book presents high-quality original contributions on new software engineering models, approaches, methods, and tools and their evaluation in the context of defence and security applications. In addition, important business and economic aspects are discussed, with a particular focus on cost/benefit analysis, new business models, organizational evolution, and business intelligence systems. The contents are based on presentations delivered at SEDA 2018, the 6th International Conference in Software Engineering for Defence Applications, which was held in Rome, Italy, in June 2018. This conference series represents a targeted response to the growing need for research that reports and debates the practical implications of software engineering within the defence environment and also for software performance evaluation in real settings through controlled experiments as well as case and field studies. The book will appeal to all with an interest in modeling, managing, and implementing defence-related software development products and processes in a structured and supportable way.

This book serves as a convenient entry point for researchers, practitioners, and students to understand the problems and challenges, learn state-of-the-art solutions for their specific needs, and quickly identify new research problems in their domains. The contributors to this volume describe the recent advancements in three related parts: (1) user engagements in the dissemination of information disorder; (2) techniques on detecting and mitigating disinformation; and (3) trending issues such as ethics, blockchain, clickbaits, etc. This edited volume will appeal to students, researchers, and professionals working on disinformation, misinformation and fake news in social media from a unique lens.