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Principles of Social Networking
This book presents new and innovative current discoveries in social networking which contribute enough knowledge to the research community. The book includes chapters presenting research advances in social network analysis and issues emerged with diverse social media data. The book also presents applications of the theoretical algorithms and network models to analyze real-world large-scale social networks and the data emanating from them as well as characterize the topology and behavior of these networks. Furthermore, the book covers extremely debated topics, surveys, future trends, issues, and challenges.
Deep Learning for Social Media Data Analytics
This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics.
Computational Data and Social Networks
This book constitutes the refereed proceedings of the 8th International Conference on Computational Data and Social Networks, CSoNet 2019, held in Ho Chi Minh City, Vietnam, in November 2019. The 22 full and 8 short papers presented in this book were carefully reviewed and selected from 120 submissions. The papers appear under the following topical headings: Combinatorial Optimization and Learning; Influence Modeling, Propagation, and Maximization; NLP and Affective Computing; Computational Methods for Social Good; and User Profiling and Behavior Modeling.
Complex Networks & Their Applications XII
Zusammenfassung: This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2023). The carefully selected papers cover a wide range of theoretical topics such as network embedding and network geometry; community structure, network dynamics; diffusion, epidemics and spreading processes; machine learning and graph neural networks as well as all the main network applications, including social and political networks; networks in finance and economics; biological networks and technological networks
Advanced Data Mining and Applications
This book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21–23, 2023. The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.
Computational Data and Social Networks
This book constitutes the refereed proceedings of the 11th International Conference on Computational Data and Social Networks, CSoNet 2022, held as a Virtual Event, during December 5–7, 2022. The 17 full papers and 7 short papers included in this book were carefully reviewed and selected from 47 submissions. They were organized in topical sections as follows: Machine Learning and Prediction, Security and Blockchain, Fact-checking, Fake News, and Hate Speech, Network Analysis, Optimization.
High Performance Computing, Smart Devices and Networks
This book comprises the proceedings of the 3rd International Conference on Computer Vision, High-Performance Computing, Smart Devices, and Networks (CHSN 2022). This book highlights high-quality research articles in machine learning, computer vision, and networks. The content of this volume gives the reader an up-to-date picture of the state-of-the-art connection between computational intelligence, machine learning, and IoT. The papers in this volume are peer-reviewed by experts in related areas. The book will serve as a valuable reference resource for academics and researchers across the globe.
Dialogues in Data Power
Available open access digitally under CC-BY-NC-ND licence. This book presents emerging themes and future directions in the interdisciplinary field of critical data studies, loosely themed around the notion of shifting response-abilities in a datafied world. In each chapter an interdisciplinary group of scholars discuss a specific theme, ranging from questions around data power and the configuring of data subjects to the intersection of technology and the environment. The book is an invaluable dialogue between disciplines that introduces readers to cutting edge arguments within the field. It will be a key resource for scholars and students who require a guide to this rapidly evolving area of research.
Complex Networks XIII
This book contains contributions presented at the 13th International Conference on Complex Networks (CompleNet), April 19–22, 2022. CompleNet is an international conference on complex networks that brings together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better understand the interdependencies within and across systems. CompleNet is a venue to discuss ideas and findings about all types of networks, from biological to technological and to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate.
