Computational Data and Social Networks
Author: Minh Hoàng Hà
Publisher: Springer Nature
Published:
Total Pages: 440
ISBN-13: 9819706696
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Computational Data and Social Networks
Author: David Mohaisen
Publisher: Springer Nature
Published: 2021-12-03
Total Pages: 392
ISBN-13: 3030914348
DOWNLOAD EBOOK →This book constitutes the refereed proceedings of the 10th International Conference on Computational Data and Social Networks, CSoNet 2021, which was held online during November 15-17, 2021. The conference was initially planned to take place in Montreal, Quebec, Canada, but changed to an online event due to the COVID-19 pandemic. The 24 full and 8 short papers included in this book were carefully reviewed and selected from 57 submissions. They were organized in topical sections as follows: Combinatorial optimization and learning; deep learning and applications to complex and social systems; measurements of insight from data; complex networks analytics; special track on fact-checking, fake news and malware detection in online social networks; and special track on information spread in social and data networks.
Computational Data and Social Networks
Author: Sriram Chellappan
Publisher: Springer Nature
Published: 2021-01-03
Total Pages: 551
ISBN-13: 303066046X
DOWNLOAD EBOOK →This book constitutes the refereed proceedings of the 9th International Conference on Computational Data and Social Networks, CSoNet 2020, held in Dallas, TX, USA, in December 2020. The 20 full papers were carefully reviewed and selected from 83 submissions. Additionally the book includes 22 special track papers and 3 extended abstracts. The selected papers are devoted to topics such as Combinatorial Optimization and Learning; Computational Methods for Social Good Applications; NLP and Affective Computing; Privacy and Security; Blockchain; Fact-Checking, Fake News and Malware Detection in Online Social Networks; and Information Spread in Social and Data Networks.
Computational Data and Social Networks
Author: Thang N. Dinh
Publisher: Springer Nature
Published: 2023-02-10
Total Pages: 313
ISBN-13: 3031263030
DOWNLOAD EBOOK →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.
Computational Data and Social Networks
Author: Minh Hoàng Hà
Publisher: Springer
Published: 2024-03-31
Total Pages: 0
ISBN-13: 9789819706686
DOWNLOAD EBOOK →This book constitutes the refereed conference proceedings of the 12th International Conference on Computational Data and Social Networks, CSoNet 2023, held in Hanoi, Vietnam, in December 2023. The 23 full papers and 14 short papers presented in this book were carefully reviewed and selected from 64 submissions. The papers are divided into the following topical sections: machine learning and prediction; optimization; security and blockchain; and network analysis.
Computational Data and Social Networks
Author: David Mohaisen
Publisher:
Published: 2021
Total Pages: 0
ISBN-13: 9783030914356
DOWNLOAD EBOOK →This book constitutes the refereed proceedings of the 10th International Conference on Computational Data and Social Networks, CSoNet 2021, which was held online during November 15-17, 2021. The conference was initially planned to take place in Montreal, Quebec, Canada, but changed to an online event due to the COVID-19 pandemic. The 24 full and 8 short papers included in this book were carefully reviewed and selected from 57 submissions. They were organized in topical sections as follows: Combinatorial optimization and learning; deep learning and applications to complex and social systems; measurements of insight from data; complex networks analytics; special track on fact-checking, fake news and malware detection in online social networks; and special track on information spread in social and data networks. .
Computational Data and Social Networks
Author: Andrea Tagarelli
Publisher: Springer Nature
Published: 2019-11-11
Total Pages: 372
ISBN-13: 3030349802
DOWNLOAD EBOOK →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.
Computational Social Networks
Author: Ajith Abraham
Publisher: Springer Science & Business Media
Published: 2012-08-14
Total Pages: 352
ISBN-13: 1447140516
DOWNLOAD EBOOK →This book is the second of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, concentrating on topics relating to security and privacy (the other two volumes review Tools, Perspectives, and Applications, and Mining and Visualization in CSNs). Topics and features: presents the latest advances in security and privacy issues in CSNs, and illustrates how both organizations and individuals can be protected from real-world threats; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, and the representation and analysis of social networks, with a focus on issues of security, privacy, and anonymization; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.
Computational Data and Social Networks
Author: Xuemin Chen
Publisher: Springer
Published: 2018-12-11
Total Pages: 544
ISBN-13: 3030046486
DOWNLOAD EBOOK →This book constitutes the refereed proceedings of the 7th International Conference on Computational Data and Social Networks, CSoNet 2018, held in Shanghai, China, in December 2018. The 44 revised full papers presented in this book toghether with 2 extended abstracts, were carefully reviewed and selected from 106 submissions. The topics cover the fundamental background, theoretical technology development, and real-world applications associated with complex and data network analysis, minimizing in uence of rumors on social networks, blockchain Markov modelling, fraud detection, data mining, internet of things (IoT), internet of vehicles (IoV), and others.
Social Network Analytics
Author: Nilanjan Dey
Publisher: Academic Press
Published: 2018-11-16
Total Pages: 267
ISBN-13: 0128156414
DOWNLOAD EBOOK →Social Network Analytics: Computational Research Methods and Techniques focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, it includes a variety of applications from several domains, such as scientific research, and the business and industrial sectors. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, the big data analytics of social networks, multidimensional scaling, and more. As analyzing social network data is rapidly gaining interest in the scientific research community because of the importance of the information and insights that can be culled from the wealth of data inherent in the various aspects of the network, this book provides insights on measuring the relationships and flows between people, groups, organizations, computers, URLs, and more. Examines a variety of data analytic techniques that can be applied to social networks Discusses various methods of visualizing, modeling and tracking network patterns, organization, growth and change Covers the most recent research on social network analysis and includes applications to a number of domains
