Computational Data And Social Networks
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Computational Data And Social Networks
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Author : Minh Hoàng Hà
language : en
Publisher: Springer Nature
Release Date : 2024-02-28
Computational Data And Social Networks written by Minh Hoàng Hà and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-28 with Computers categories.
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
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Author : Janos Kertesz
language : en
Publisher: Springer
Release Date : 2025-06-03
Computational Data And Social Networks written by Janos Kertesz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-03 with Computers categories.
This book constitutes the refereed conference proceedings of the 13th International Conference on Computational Data and Social Networks, CSoNet 2024, held in Bangkok, Thailand, during December 16–18, 2024. The 18 full papers and 17 short papers presented in this volume were carefully reviewed and selected from 50 submissions. These papers deal with various aspects of computational data and social networks, focusing on large-scale network computing, data network analysis, mining, security and privacy, optimization, and learning.
Computational Data And Social Networks
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Author : Thang N. Dinh
language : en
Publisher: Springer Nature
Release Date : 2023-02-10
Computational Data And Social Networks written by Thang N. Dinh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-10 with Computers categories.
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
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Author : Xuemin Chen
language : en
Publisher: Springer
Release Date : 2018-12-11
Computational Data And Social Networks written by Xuemin Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-11 with Computers categories.
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.
Computational Data And Social Networks
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Author : David Mohaisen
language : en
Publisher: Springer Nature
Release Date : 2021-12-03
Computational Data And Social Networks written by David Mohaisen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-03 with Computers categories.
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
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Author : Andrea Tagarelli
language : en
Publisher: Springer Nature
Release Date : 2019-11-11
Computational Data And Social Networks written by Andrea Tagarelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-11 with Computers categories.
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 Data And Social Networks
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Author : Janos Kertesz
language : en
Publisher: Springer Nature
Release Date : 2025-06-06
Computational Data And Social Networks written by Janos Kertesz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.
This book constitutes the refereed conference proceedings of the 13th International Conference on Computational Data and Social Networks, CSoNet 2024, held in Bangkok, Thailand, during December 16–18, 2024. The 18 full papers and 17 short papers presented in this volume were carefully reviewed and selected from 50 submissions. These papers deal with various aspects of computational data and social networks, focusing on large-scale network computing, data network analysis, mining, security and privacy, optimization, and learning.
Computational Data And Social Networks
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Author : Sriram Chellappan
language : en
Publisher: Springer Nature
Release Date : 2021-01-03
Computational Data And Social Networks written by Sriram Chellappan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-03 with Computers categories.
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
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Author : David Mohaisen
language : en
Publisher:
Release Date : 2021
Computational Data And Social Networks written by David Mohaisen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Application software categories.
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. .
Data Mining Approaches For Big Data And Sentiment Analysis In Social Media
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Author : Gupta, Brij B.
language : en
Publisher: IGI Global
Release Date : 2021-12-31
Data Mining Approaches For Big Data And Sentiment Analysis In Social Media written by Gupta, Brij B. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-31 with Computers categories.
Social media sites are constantly evolving with huge amounts of scattered data or big data, which makes it difficult for researchers to trace the information flow. It is a daunting task to extract a useful piece of information from the vast unstructured big data; the disorganized structure of social media contains data in various forms such as text and videos as well as huge real-time data on which traditional analytical methods like statistical approaches fail miserably. Due to this, there is a need for efficient data mining techniques that can overcome the shortcomings of the traditional approaches. Data Mining Approaches for Big Data and Sentiment Analysis in Social Media encourages researchers to explore the key concepts of data mining, such as how they can be utilized on online social media platforms, and provides advances on data mining for big data and sentiment analysis in online social media, as well as future research directions. Covering a range of concepts from machine learning methods to data mining for big data analytics, this book is ideal for graduate students, academicians, faculty members, scientists, researchers, data analysts, social media analysts, managers, and software developers who are seeking to learn and carry out research in the area of data mining for big data and sentiment.