Bøger i Lecture Notes in Social Networks serien

This edited volume offers a clear in-depth overview of research covering a variety of issues in social search and recommendation systems.

This book offers an excellent source of knowledge for readers who are interested in keeping up with the developments in the field of cyber security and social media analysis. It covers the possibility of using augmented reality to monitor cyber security feeds in a multitasking environment. It describes a real-time scheduled security scanner. E-commerce concept labeling is tackled by introducing a lightweight global taxonomy induction system. Blogsphere analytics and online video narratives and networks are explored. The effect of global and local network structure, credibility based prevention of fake news dissemination, and detection of trending topics and influence from social media are investigated.This book helps the reader in developing their own perspective about how to deal with cyber security and how to benefit from the development in technology to tackle cyber security issues. The reader of this book will realize how to use various machine learning techniques for tackling various applications involving social medial analysis.

Network Analysis Literacy focuses on design principles for network analytics projects. The text enables readers to: pose a defined network analytic question; build a network to answer the question; choose or design the right network analytic methods for a particular purpose, and more.

Through a detailed critique of existing online social networks, this volume presents the technical and methodological aspects of designing social media platforms and applications. Readers will learn current techniques and best practices for designing and implementing social networks on the web.

The topics cover generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, behavior detection, mining social content for common trends, identifying and ranking social content sources, building friend-comprehension tools, and many others.

This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. general aspects of social networks such as pattern and anomaly detection;

Important aspects of social networking analysis are covered in this work by combining experimental and theoretical research.

This book shows how open source intelligence can be a powerful tool for combating crime by linking local and global patterns to help understand how criminal activities are connected. Readers will encounter the latest advances in cutting-edge data mining, machine learning and predictive analytics combined with natural language processing and social network analysis to detect, disrupt, and neutralize cyber and physical threats. Chapters contain state-of-the-art social media analytics and open source intelligence research trends. This multidisciplinary volume will appeal to students, researchers, and professionals working in the fields of open source intelligence, cyber crime and social network analytics. Chapter Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health.

The study of social networks was originated in social and business communities.

The present work will discuss relevant theoretical frameworks and applications pertaining to enabling resilience within the risk, crisis and disaster management domain. This will be of particular interest to those working in the risk, crisis and disaster management domain as it will provide valuable insights into enabling resilience.

The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health.

State of the Art Applications of Social Network Analysis

The study of social networks was originated in social and business communities.

This book presents the state-of-the-art in various aspects of analysis and mining of online social networks.

This book addresses the challenges of social network and social media analysis in terms of prediction and inference. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection.

The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking.

The present work will discuss relevant theoretical frameworks and applications pertaining to enabling resilience within the risk, crisis and disaster management domain. This will be of particular interest to those working in the risk, crisis and disaster management domain as it will provide valuable insights into enabling resilience.

This book focuses on applications of social network analysis in predictive policing. Despite the importance of co-offending network analysis for public safety, computational methods for analyzing large-scale criminal networks are rather premature.

This edited volume offers a clear in-depth overview of research covering a variety of issues in social search and recommendation systems.

In this context, this book provides a state-of-the-art survey of the most recent advances in the field of counterterrorism and open source intelligence, demonstrating how various existing as well as novel tools and techniques can be applied in combating covert terrorist networks.

In this context, this book provides a state-of-the-art survey of the most recent advances in the field of counterterrorism and open source intelligence, demonstrating how various existing as well as novel tools and techniques can be applied in combating covert terrorist networks.

This book focuses on recent technical advancements and state-of-the art technologies for analyzing characteristic features and probabilistic modelling of complex social networks and decentralized online network architectures.

This book addresses the challenges of social network and social media analysis in terms of prediction and inference. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection.

The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis.

This book focuses on recent technical advancements and state-of-the art technologies for analyzing characteristic features and probabilistic modelling of complex social networks and decentralized online network architectures.

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.

This book is related to the educational networking (EN) domain, an incipient but disrupting trend engaged in extending and improving formal and informal academic practices by means of the support given by online social networks (OSNs) and Web 2.0 technologies. With the aim of contributing to spread the knowledge and development of the arena, this volume introduces ten recent works, whose content meets the quality criteria of formal scientific labor that is worthy to be published according to following five categories:┬╖         Reviews: gather three overviews that focus on K-12 EN practice, mixed methods approaches using social network analysis for learning and education, and a broad landscape of the recent accomplished labor.┬╖         Conceptual: presents a work where a theoretical framework is proposed to overcome barriers that constrain the use of OSNs for educational purposes by means of a Platform Adoption Model. ┬╖         Projects: inform a couple of initiatives, where one fosters groups and networks for teachers involved in distance education, and the other encourages students the author academic videos to improve motivation and engagement.┬╖         Approaches: offer three experiences related to: Wiki and Blog usage for assessment affairs, application of a method that encourages OSNs users to actively post and repost valuable information for the learning community, and the recreation of learning spaces in contextΓÇôaware to boost EN.┬╖         Study: applies an own method to ranking Mexican universities based on maximal clique, giving as a result a series of complex visual networks that characterize the tides among diverse features that describe academic institutions practice.In resume, this volume offers a fresh reference of an emergent field that contributes to spreading and enhancing the provision of education in classrooms and online settings through social constructivism and collaboration policy. Thus, it is expected the published content encourages researchers, practitioners, professors, and postgraduate students to consider their future contribution to extent the scope and impact of EN in formal and informal teaching and learning endeavors.

This book addresses and examines the impacts of applications and services for data management and analysis, such as infrastructure, platforms, software, and business processes, on both academia and industry.