Modeling Information Diffusion In Online Social Networks With Partial Differential Equations

Author : Haiyan Wang,Feng Wang,Kuai Xu
Publisher : Springer Nature
Page : 153 pages
File Size : 53,9 Mb
Release : 2020-03-16
Category : Mathematics
ISBN : 9783030388522

Get Book

Modeling Information Diffusion in Online Social Networks with Partial Differential Equations by Haiyan Wang,Feng Wang,Kuai Xu Pdf

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.

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 920 pages
File Size : 41,7 Mb
Release : 2019-10-11
Category : Computers
ISBN : 9781799804185

Get Book

Information Diffusion Management and Knowledge Sharing: Breakthroughs in Research and Practice by Management Association, Information Resources Pdf

Within the past 10 years, tremendous innovations have been brought forth in information diffusion and management. Such technologies as social media have transformed the way that information is disseminated and used, making it critical to understand its distribution through these mediums. With the consistent creation and wide availability of information, it has become imperative to remain updated on the latest trends and applications in this field. Information Diffusion Management and Knowledge Sharing: Breakthroughs in Research and Practice examines the trends, models, challenges, issues, and strategies of information diffusion and management from a global context. Highlighting a range of topics such as influence maximization, information spread control, and social influence, this publication is an ideal reference source for managers, librarians, information systems specialists, professionals, researchers, and administrators seeking current research on the theories and applications of global information management.

Author : Ngoc Thanh Nguyen,Duong Hung Hoang,Tzung-Pei Hong,Hoang Pham,Bogdan Trawiński
Publisher : Springer
Page : 749 pages
File Size : 49,9 Mb
Release : 2018-03-03
Category : Computers
ISBN : 9783319754178

Get Book

Intelligent Information and Database Systems by Ngoc Thanh Nguyen,Duong Hung Hoang,Tzung-Pei Hong,Hoang Pham,Bogdan Trawiński Pdf

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.

Author : Jingli Ren,Haiyan Wang
Publisher : Elsevier
Page : 260 pages
File Size : 41,7 Mb
Release : 2023-01-06
Category : Computers
ISBN : 9780443186806

Get Book

Mathematical Methods in Data Science by Jingli Ren,Haiyan Wang Pdf

Mathematical Methods in Data Science covers a broad range of mathematical tools used in data science, including calculus, linear algebra, optimization, network analysis, probability and differential equations. Based on the authors’ recently published and previously unpublished results, this book introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for dataanalysis and prediction. With data science being used in virtually every aspect of our society, the book includes examples and problems arising in data science and the clear explanation of advanced mathematical concepts, especially data-driven differential equations, making it accessible to researchers and graduate students in mathematics and data science. Combines a broad spectrum of mathematics, including linear algebra, optimization, network analysis and ordinary and partial differential equations for data science Written by two researchers who are actively applying mathematical and statistical methods as well as ODE and PDE for data analysis and prediction Highly interdisciplinary, with content spanning mathematics, data science, social media analysis, network science, financial markets, and more Presents a wide spectrum of topics in a logical order, including probability, linear algebra, calculus and optimization, networks, ordinary differential and partial differential equations

Author : Shumon Koga,Miroslav Krstic
Publisher : Springer Nature
Page : 352 pages
File Size : 44,8 Mb
Release : 2020-11-01
Category : Science
ISBN : 9783030584900

Get Book

Materials Phase Change PDE Control & Estimation by Shumon Koga,Miroslav Krstic Pdf

This monograph introduces breakthrough control algorithms for partial differential equation models with moving boundaries, the study of which is known as the Stefan problem. The algorithms can be used to improve the performance of various processes with phase changes, such as additive manufacturing. Using the authors' innovative design solutions, readers will also be equipped to apply estimation algorithms for real-world phase change dynamics, from polar ice to lithium-ion batteries. A historical treatment of the Stefan problem opens the book, situating readers in the larger context of the area. Following this, the chapters are organized into two parts. The first presents the design method and analysis of the boundary control and estimation algorithms. Part two then explores a number of applications, such as 3D printing via screw extrusion and laser sintering, and also discusses the experimental verifications conducted. A number of open problems and provided as well, offering readers multiple paths to explore in future research. Materials Phase Change PDE Control & Estimation is ideal for researchers and graduate students working on control and dynamical systems, and particularly those studying partial differential equations and moving boundaries. It will also appeal to industrial engineers and graduate students in engineering who are interested in this area.

Author : Wei Chen,Carlos Castillo,Laks V.S. Lakshmanan
Publisher : Springer Nature
Page : 161 pages
File Size : 53,7 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031018503

Get Book

Information and Influence Propagation in Social Networks by Wei Chen,Carlos Castillo,Laks V.S. Lakshmanan Pdf

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.

Author : Alexander Strekalovsky,Yury Kochetov,Tatiana Gruzdeva,Andrei Orlov
Publisher : Springer Nature
Page : 515 pages
File Size : 49,5 Mb
Release : 2021-09-20
Category : Mathematics
ISBN : 9783030864330

Get Book

Mathematical Optimization Theory and Operations Research: Recent Trends by Alexander Strekalovsky,Yury Kochetov,Tatiana Gruzdeva,Andrei Orlov Pdf

This book constitutes refereed proceedings of the 20th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2021, held in Irkutsk, Russia, in July 2021. Due to the COVID-19 pandemic the conference was held online. The 31 full papers and 3 short papers presented in this volume were carefully reviewed and selected from a total of 102 submissions. The papers in the volume are organised according to the following topical headings: continuous optimization; integer programming and combinatorial optimization; operational research applications; optimal control.

Author : Michael Muhlmeyer,Shaurya Agarwal
Publisher : CRC Press
Page : 252 pages
File Size : 43,9 Mb
Release : 2021-03-29
Category : Computers
ISBN : 9780429558870

Get Book

Information Spread in a Social Media Age by Michael Muhlmeyer,Shaurya Agarwal Pdf

The rise of social networks and social media has led to a massive shift in the ways information is dispersed. Platforms like Twitter and Facebook allow people to more easily connect as a community, but they can also be avenues for misinformation, fake news, and polarization. The need to examine, model, and analyze the trajectory of information spread within this new paradigm has never been greater. This text expands upon the authors’ combined teaching experience, engineering knowledge, and multiple academic journal publications on these topics to present an intuitive and easy to understand exploration of social media information spread alongside the technical and mathematical concepts. By design, this book uses simple language and accessible and modern case studies (including those centered around United States mass shootings, the #MeToo social movement, and more) to ensure it is accessible to the casual reader. At the same time, readers with prior knowledge of the topics will benefit from the mathematical model and control elements and accompanying sample simulation code for each main topic. By reading this book and working through the included exercises, readers will gain a general understanding of modern social media systems, network fundamentals, model development techniques, and social marketing. The mathematical modeling of information spread over social media is heavily emphasized through a review of existing epidemiology and marketing based models. The book then presents novel models developed by the authors to account for modern social media concerns such as community filter bubbles, strongly polarized groups, and contentious information spread. Readers will learn how to build and execute simple case studies using Twitter data to help verify the text’s proposed models. Once the reader is armed with a fundamental understanding of mathematical modeling and social media-based system considerations, the book introduces more complex engineering control concepts, including controller design, PID control, and optimal control. Examples of control methods for social campaigns and misinformation mitigation applications are covered in a step-by-step format from problem formulation to solution simulation and results discussions. While many of the examples and methods are framed in the context of controlling social media information spread, the material is also directly applicable to many different types of controllable systems. With the essential background, models, and tools presented within, any interested reader can take the first steps toward exploring and taming the growing complexity of the modern social media age.

Author : Hongxian Sun
Publisher : Unknown
Page : 0 pages
File Size : 45,6 Mb
Release : 2012
Category : Social networks
ISBN : OCLC:815996167

Get Book

Modeling Information Diffusion in Social Networks by Hongxian Sun Pdf

Author : Sriram Chellappan,Kim-Kwang Raymond Choo,NhatHai Phan
Publisher : Springer Nature
Page : 551 pages
File Size : 44,5 Mb
Release : 2021-01-03
Category : Computers
ISBN : 9783030660468

Get Book

Computational Data and Social Networks by Sriram Chellappan,Kim-Kwang Raymond Choo,NhatHai Phan Pdf

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.

Author : Paulo Shakarian,Abhivav Bhatnagar,Ashkan Aleali,Elham Shaabani,Ruocheng Guo
Publisher : Springer
Page : 101 pages
File Size : 53,6 Mb
Release : 2015-09-16
Category : Computers
ISBN : 9783319231051

Get Book

Diffusion in Social Networks by Paulo Shakarian,Abhivav Bhatnagar,Ashkan Aleali,Elham Shaabani,Ruocheng Guo Pdf

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.

Author : Valerio Arnaboldi,Andrea Passarella,Marco Conti,Robin I.M. Dunbar
Publisher : Elsevier
Page : 116 pages
File Size : 48,6 Mb
Release : 2015-09-25
Category : Computers
ISBN : 9780128030424

Get Book

Online Social Networks by Valerio Arnaboldi,Andrea Passarella,Marco Conti,Robin I.M. Dunbar Pdf

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

Author : Jingli Ren,Haiyan Wang
Publisher : Elsevier
Page : 258 pages
File Size : 51,7 Mb
Release : 2023-01-16
Category : Computers
ISBN : 9780443186790

Get Book

Mathematical Methods in Data Science by Jingli Ren,Haiyan Wang Pdf

Mathematical Methods in Data Science introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for data analysis and prediction. The mathematics is accompanied with examples and problems arising in data science to demonstrate advanced mathematics, in particular, data-driven differential equations used. Chapters also cover network analysis, ordinary and partial differential equations based on recent published and unpublished results. Finally, the book introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for data analysis and prediction. There are a number of books on mathematical methods in data science. Currently, all these related books primarily focus on linear algebra, optimization and statistical methods. However, network analysis, ordinary and partial differential equation models play an increasingly important role in data science. With the availability of unprecedented amount of clinical, epidemiological and social COVID-19 data, data-driven differential equation models have become more useful for infection prediction and analysis. Combines a broad spectrum of mathematics, including linear algebra, optimization, network analysis and ordinary and partial differential equations for data science Written by two researchers who are actively applying mathematical and statistical methods as well as ODE and PDE for data analysis and prediction Highly interdisciplinary, with content spanning mathematics, data science, social media analysis, network science, financial markets, and more Presents a wide spectrum of topics in a logical order, including probability, linear algebra, calculus and optimization, networks, ordinary differential and partial differential equations

Author : Alexander G. Chkhartishvili,Dmitry A. Gubanov,Dmitry A. Novikov
Publisher : Springer
Page : 158 pages
File Size : 52,7 Mb
Release : 2018-12-30
Category : Technology & Engineering
ISBN : 9783030054298

Get Book

Social Networks: Models of Information Influence, Control and Confrontation by Alexander G. Chkhartishvili,Dmitry A. Gubanov,Dmitry A. Novikov Pdf

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.

Author : Ngoc Thanh Nguyen,Duong Hung Hoang,Tzung-Pei Hong,Hoang Pham,Bogdan Trawiński
Publisher : Springer
Page : 0 pages
File Size : 40,8 Mb
Release : 2018-02-15
Category : Computers
ISBN : 3319754165

Get Book

Intelligent Information and Database Systems by Ngoc Thanh Nguyen,Duong Hung Hoang,Tzung-Pei Hong,Hoang Pham,Bogdan Trawiński Pdf

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.