Modeling Information Diffusion In Social Networks
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Diffusion In Social Networks
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Author : Paulo Shakarian
language : en
Publisher: Springer
Release Date : 2015-09-16
Diffusion In Social Networks written by Paulo Shakarian and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-16 with Computers categories.
This book presents the leading models of social network diffusion that are used to demonstrate the spread of disease, ideas, and behavior. It introduces diffusion models from the fields of computer science (independent cascade and linear threshold), sociology (tipping models), physics (voter models), biology (evolutionary models), and epidemiology (SIR/SIS and related models). A variety of properties and problems related to these models are discussed including identifying seeds sets to initiate diffusion, game theoretic problems, predicting diffusion events, and more. The book explores numerous connections between social network diffusion research and artificial intelligence through topics such as agent-based modeling, logic programming, game theory, learning, and data mining. The book also surveys key empirical results in social network diffusion, and reviews the classic and cutting-edge research with a focus on open problems.
Online Social Networks
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Author : Valerio Arnaboldi
language : en
Publisher: Elsevier
Release Date : 2015-09-25
Online Social Networks written by Valerio Arnaboldi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-25 with Computers categories.
Online Social Networks: Human Cognitive Constraints in Facebook and Twitter provides new insights into the structural properties of personal online social networks and the mechanisms underpinning human online social behavior. As the availability of digital communication data generated by social media is revolutionizing the field of social networks analysis, the text discusses the use of large- scale datasets to study the structural properties of online ego networks, to compare them with the properties of general human social networks, and to highlight additional properties. Users will find the data collected and conclusions drawn useful during design or research service initiatives that involve online and mobile social network environments. - Provides an analysis of the structural properties of ego networks in online social networks - Presents quantitative evidence of the Dunbar's number in online environments - Discusses original structural and dynamic properties of human social network through OSN analysis
Modeling Information Diffusion In Social Networks
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Author : Hongxian Sun
language : en
Publisher:
Release Date : 2012
Modeling Information Diffusion In Social Networks written by Hongxian Sun and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Social networks categories.
Modeling Information Diffusion In Online Social Networks With Partial Differential Equations
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Author : Haiyan Wang
language : en
Publisher: Springer Nature
Release Date : 2020-03-16
Modeling Information Diffusion In Online Social Networks With Partial Differential Equations written by Haiyan Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-16 with Mathematics categories.
The book lies at the interface of mathematics, social media analysis, and data science. Its authors aim to introduce a new dynamic modeling approach to the use of partial differential equations for describing information diffusion over online social networks. The eigenvalues and eigenvectors of the Laplacian matrix for the underlying social network are used to find communities (clusters) of online users. Once these clusters are embedded in a Euclidean space, the mathematical models, which are reaction-diffusion equations, are developed based on intuitive social distances between clusters within the Euclidean space. The models are validated with data from major social media such as Twitter. In addition, mathematical analysis of these models is applied, revealing insights into information flow on social media. Two applications with geocoded Twitter data are included in the book: one describing the social movement in Twitter during the Egyptian revolution in 2011 and another predicting influenza prevalence. The new approach advocates a paradigm shift for modeling information diffusion in online social networks and lays the theoretical groundwork for many spatio-temporal modeling problems in the big-data era.
Python For Graph And Network Analysis
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Author : Mohammed Zuhair Al-Taie
language : en
Publisher: Springer
Release Date : 2017-03-20
Python For Graph And Network Analysis written by Mohammed Zuhair Al-Taie and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-20 with Computers categories.
This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego, group, and community. They will be able to analyse militant and revolutionary networks and candidate networks during elections. For instance, they will learn how the Ebola virus spread through communities. Practically, the book is suitable for courses on social network analysis in all disciplines that use social methodology. In the study of social networks, social network analysis makes an interesting interdisciplinary research area, where computer scientists and sociologists bring their competence to a level that will enable them to meet the challenges of this fast-developing field. Computer scientists have the knowledge to parse and process data while sociologists have the experience that is required for efficient data editing and interpretation. Social network analysis has successfully been applied in different fields such as health, cyber security, business, animal social networks, information retrieval, and communications.
Modeling Information Diffusion In Social Networks
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Author : Hongxian Sun
language : en
Publisher:
Release Date : 2012
Modeling Information Diffusion In Social Networks written by Hongxian Sun and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Social networks categories.
Social Networks
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Author : Niyati Aggrawal
language : en
Publisher: CRC Press
Release Date : 2024-10-04
Social Networks written by Niyati Aggrawal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-04 with Computers categories.
The goal of this book is to provide a reference for applications of mathematical modelling in social media and related network analysis and offer a theoretically sound background with adequate suggestions for better decision-making.
Models And Methods In Social Network Analysis
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Author : Peter J. Carrington
language : en
Publisher:
Release Date : 2005-02-07
Models And Methods In Social Network Analysis written by Peter J. Carrington and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02-07 with Psychology categories.
Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.
Network Models Of The Diffusion Of Innovations
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Author : Thomas W. Valente
language : en
Publisher:
Release Date : 1995
Network Models Of The Diffusion Of Innovations written by Thomas W. Valente and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Language Arts & Disciplines categories.
This text presents a key to understanding how ideas, products and opinions take off and spread throughout society - referred to as the diffusion of innovation - and provides a means to estimate how fast or slow that spread occurs. The diffusion of innovations occurs among individuals in a social system, and the pattern of communications among these individuals is a social network. The network determines how quickly innovations diffuse and the timing of each individual's adoption. The book thus analyses how social networks structure the diffusion of innovation.
Intelligent Information And Database Systems
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Author : Ngoc Thanh Nguyen
language : en
Publisher: Springer
Release Date : 2018-03-03
Intelligent Information And Database Systems written by Ngoc Thanh Nguyen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-03 with Computers categories.
The two-volume set LNAI 10751 and 10752 constitutes the refereed proceedings of the 10th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2018, held in Dong Hoi City, Vietnam, in March 2018. The total of 133 full papers accepted for publication in these proceedings was carefully reviewed and selected from 423 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Machine Learning and Data Mining; Decision Support and Control Systems; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Multiple Model Approach to Machine Learning; Sensor Networks and Internet of Things; Intelligent Information Systems; Data Structures Modeling for Knowledge Representation; Modeling, Storing, and Querying of Graph Data; Data Science and Computational Intelligence; Design Thinking Based R&D, Development Technique, and Project Based Learning; Intelligent and Contextual Systems; Intelligent Systems and Algorithms in Information Sciences; Intelligent Applications of Internet of Thing and Data Analysis Technologies; Intelligent Systems and Methods in Biomedicine; Intelligent Biomarkers of Neurodegenerative Processes in Brain; Analysis of Image, Video and Motion Data in Life Sciences; Computational Imaging and Vision; Computer Vision and Robotics; Intelligent Computer Vision Systems and Applications; Intelligent Systems for Optimization of Logistics and Industrial Applications.