Information And Influence Propagation In Social Networks
DOWNLOAD
Download Information And Influence Propagation In Social Networks PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Information And Influence Propagation In Social Networks book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Information And Influence Propagation In Social Networks
DOWNLOAD
Author : Wei Chen
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2013-10-01
Information And Influence Propagation In Social Networks written by Wei Chen and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-01 with Computers categories.
Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models against any available real datasets consisting of a social network and propagation traces that occurred in the past? These are just some questions studied by researchers in this area. Information propagation models find applications in viral marketing, outbreak detection, finding key blog posts to read in order to catch important stories, finding leaders or trendsetters, information feed ranking, etc. A number of algorithmic problems arising in these applications have been abstracted and studied extensively by researchers under the garb of influence maximization. This book starts with a detailed description of well-established diffusion models, including the independent cascade model and the linear threshold model, that have been successful at explaining propagation phenomena. We describe their properties as well as numerous extensions to them, introducing aspects such as competition, budget, and time-criticality, among many others. We delve deep into the key problem of influence maximization, which selects key individuals to activate in order to influence a large fraction of a network. Influence maximization in classic diffusion models including both the independent cascade and the linear threshold models is computationally intractable, more precisely #P-hard, and we describe several approximation algorithms and scalable heuristics that have been proposed in the literature. Finally, we also deal with key issues that need to be tackled in order to turn this research into practice, such as learning the strength with which individuals in a network influence each other, as well as the practical aspects of this research including the availability of datasets and software tools for facilitating research. We conclude with a discussion of various research problems that remain open, both from a technical perspective and from the viewpoint of transferring the results of research into industry strength applications.
Information And Influence Propagation In Social Networks
DOWNLOAD
Author : Wei Chen
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Information And Influence Propagation In Social Networks written by Wei Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models against any available real datasets consisting of a social network and propagation traces that occurred in the past? These are just some questions studied by researchers in this area. Information propagation models find applications in viral marketing, outbreak detection, finding key blog posts to read in order to catch important stories, finding leaders or trendsetters, information feed ranking, etc. A number of algorithmic problems arising in these applications have been abstracted and studied extensively by researchers under the garb of influence maximization. This book starts with a detailed description of well-established diffusion models, including the independent cascade model and the linear threshold model, that have been successful at explaining propagation phenomena. We describe their properties as well as numerous extensions to them, introducing aspects such as competition, budget, and time-criticality, among many others. We delve deep into the key problem of influence maximization, which selects key individuals to activate in order to influence a large fraction of a network. Influence maximization in classic diffusion models including both the independent cascade and the linear threshold models is computationally intractable, more precisely #P-hard, and we describe several approximation algorithms and scalable heuristics that have been proposed in the literature. Finally, we also deal with key issues that need to be tackled in order to turn this research into practice, such as learning the strength with which individuals in a network influence each other, as well as the practical aspects of this research including the availability of datasets and software tools for facilitating research. We conclude with a discussion of various research problems that remain open, both from a technical perspective and from the viewpoint of transferring the results of research into industry strength applications.
Trends In Social Network Analysis
DOWNLOAD
Author : Rokia Missaoui
language : en
Publisher: Springer
Release Date : 2017-04-29
Trends In Social Network Analysis written by Rokia Missaoui and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-29 with Computers categories.
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. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.
Diffusion In Social Networks
DOWNLOAD
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.
Workshop Proceedings Of The 13th International Aaai Conference On Web And Social Media
DOWNLOAD
Author : Emilio Zagheni
language : en
Publisher: Frontiers Media SA
Release Date : 2020-07-31
Workshop Proceedings Of The 13th International Aaai Conference On Web And Social Media written by Emilio Zagheni and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-31 with Science categories.
Social Networks Models Of Information Influence Control And Confrontation
DOWNLOAD
Author : Alexander G. Chkhartishvili
language : en
Publisher: Springer
Release Date : 2018-12-30
Social Networks Models Of Information Influence Control And Confrontation written by Alexander G. Chkhartishvili and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-30 with Technology & Engineering categories.
This book surveys the well-known results and also presents a series of original results on the mathematical modeling of social networks, focusing on models of informational influence, control and confrontation. Online social networks are intended for communication, opinion exchange and information acquisition for their members, but recently, online social networks have been intensively used as the objects and means of informational control and an arena of informational confrontation. They have become a powerful informational influence tool, particularly for the manipulation of individuals, social groups and society as a whole, as well as a battlefield of information warfare (cyberwars). This book aimed at under- and postgraduate university students as well as experts in information technology and modeling of social systems and processes.
Computational Data And Social Networks
DOWNLOAD
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
DOWNLOAD
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 Social Networks
DOWNLOAD
Author : My T. Thai
language : en
Publisher: Springer
Release Date : 2015-07-30
Computational Social Networks written by My T. Thai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-30 with Computers categories.
This book constitutes the refereed proceedings of the 4th International Conference on Computational Social Networks, CSoNet 2015, held in Beijing, China, in August 2015. The 23 revised full papers and 3 short papers presented together with 2 extended abstracts were carefully reviewed and selected from 101 submissions and cover topics on social information diffusion; network clustering and community structure; social link prediction and recommendation; and social network structure analysis.
Computational Data And Social Networks
DOWNLOAD
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.