Information spread in a social media age modeling and control
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| Format: | Buch |
| Sprache: | English |
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Boca Raton ; London ; New York
CRC Press, Taylor & Francis Group
2021
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| Ausgabe: | First edition |
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| adam_text | Contents xiii Foreword Preface xv xvii Authors Acknowledgments xix List of Figures xxi List of Tables xxv List of Codes xxvii Symbols xxix 1 Introduction 1.1 Expressions of Information ..................................................... 1.2 Why Information Spread Matters?.......................................... 1.3 Modern Information Spread Scenarios.................................... 1.3.1 Global Communication During a Pandemic............... 1.3.2 Governments and Mass Panic....................................... 1.3.3 Shopping and Advertising............................................... 1.3.4 Social or Political Campaigning....................................... 1.3.5 Misinformation, Disinformation, and Fake News ... 1.4 Controllable Information Spread ............................................. 1.5 How to Read This Book........................................................... 1.6 Exercises ...................................................................................... I Understanding Social Networking Systems 1 2 5 5 6 6 7 7 8 9 10 11 13 2 Social Media in Popular Culture 15 2.1 The Topology of Social Media ............................................... 15 2.2 Social Networking Sites.............................................................. 17 2.2.1 Twitter.............................................................................. 17 2.2.2 Facebook........................................................................... 17 2.2.3 LinkedIn........................................................................... 18 2.3 Content Sharing
Sites.............................................................. 18 vii
v^* Contents Discussion Forums............................................................................. 2.4 News and Blogs ......................................................................... Shopping and Reviews ............................................................. Games and Music .......................................................................... Hybrid Social Media....................................................................... 2.8.1 Internet Memes................................................................ 2.9 Exercises ...................................................................................... 2.5 2.G 2.7 2.8 3 19 ig 20 21 21 22 23 Social Theory and Networks 25 Philosophy. Science, and Information Spread ........................ 3.1.1 The Ancient World......................................................... 3.1.2 The Medieval World...................................................... 3.1.3 The Early Modern World................................................ 3.1.4 The Contemporary World............................................. 3.2 Social Theory and Social Networks ....................................... 3.3 Social Exchange Theory............................................................ 3.4 Exercises .................................................................................... 25 26 26 27 28 29 30 32 3.1 4 Social Network Relationships and Structures 4.1 4.2 Social Network Relationship Overview.................................... Core Social Network Relationships..........................................
4.2.1 Symmetry........................................................................ 4.2.2 Directionality.................................................................. 4.2.3 Intermediary Relationships .......................................... 4.2.4 Complex Networks......................................................... Homophile and Filter Bubbles ................................................. Dyadic Relationships and Reciprocity ........................................ Triads and Balanced Relationships........................................... Social Network Analysis Software ........................................... Exercises ...................................................................................... 4.3 4.4 4.5 4.6 4.7 5 Social Network Analysis 5.1 5.2 5.3 5.4 5.5 5.6 5.7 II Density and Structural Holes.................................................. Weak and Strong Ties.............................................................. Centrality and Distance........................................................... Small World Networks.............................................................. Clusters, Cohesion, and Polarization...................................... The Adjacency Matrix ........................................................... 5.6.1 Example: A Fencing Club Sociogram........................... Exercises ................................................................................... Macroscopic Modeling and Information Spread 33 33 34 34 34 34 3a 36 37 38 39 41 43 43 46 46 48 50 52 53 55 57
Contents 6 Modeling Basics 6.1 What is a Model? .......................................................................... 6.2 Models in Decision Making......................................................... 6.3 Standard Models............................................................................... 6.4 Models, Assumptions, and Approximations ............................ 6.5 Mathematical Systems Modeling............................................... 6.6 Microscopic and Macroscopic Models .................................... 6.7 Basic Steps to Develop a MathematicalModel ....................... 6.8 Model Validation ............................................................................ 6.9 Modeling and the State-Space Representation ........................ 6.10 Example 1: A Spring-Mass System............................................ 6.11 Example 2: A Predator-Prey System............................................ 6.12 Example 3: An RLC Circuit ..................................................... 6.13 Example 4: An Epidemic Model ............................................... 6.14 Example 5: Vehicular Traffic Modeling .................................... 6.14.1 LWR and Greenshields’ Models for Traffic....................... 6.14.2 ODE Approximation of LWR Model............................. 6.15 Exercises ............................................................................................ ix 59 59 60 61 63 64 64 66 67 67 70 71 73 74 76 77 78 81 7 Epidemiology-Based Models for Information Spread 85 7.1 Epidemiology Models
.................................................................. 85 7.1.1 The SIR. Disease Spread Model....................................... 86 7.1.2 The SEIR Disease Spread Model.................................... 89 7.1.3 Herd Immunity in Epidemiology.................................... 90 7.1.4 Flattening the Curve ....................................................... 91 7.1.5 Epidemiology Models as Analog Models....................... 93 7.2 Information Spread Models: Overview and Conventions ... 94 7.3 The Ignorant-Spreader Model .................................................... 95 7.4 The Ignorant-Spreader-Ignorant (ISI) Model ............................. 97 7.5 The Ignorant-Spreader-Recovered (ISR) Model ................... 99 7.6 Reproductive Number and Herd Immunity ....................................101 7.7 ISR Model for Social Media.......................................................... 103 7.7.1 ISR Model for Social Media with Decay....................... 106 7.8 ISCR Model for Contentious Information Spread.......................... 107 7.9 Hybrid ISCR Model........................................................................ 115 7.10 ISSRR Model for Contentious Information .................................... 121 7.11 Exercises ................................................................................................. 127 8 Stochastic Modeling of Information Spread 129 8.1 Brownian Motion ........................................................................... 130 8.2 Deterministic and Stochastic Realizations of
Processes..............131 8.3 Stochastic Modeling Considerations for Social MediaSystems 132 8.4 Stochastic ISI Information Model .............................................. 133 8.5 Stochastic ISR Information Modeling and Social Media . . . 135 8.6 Exercises ................................................................................................. 137
Contents 9 Social Marketing-Based Models for Information Spread 139 9.1 Vidale-Wolf Model ....................................................................... 141 9.2 Bass Model.................................................... ,........................... 142 9.3 Sethi Model .............................................................................. 142 9.4 Event-triggered Social Media Chatter Model ....................... 144 9.4.1 Socio-Equilibrium Threshold ....................................... 146 9.4.2 Simulation and Discussion................................................... 147 9.5 Exercises ............................. 152 10 Case Studies 153 10.1 Selecting Case Studies................................................................ 154 10.2 Case Study-1: 2017 Mass Shootings ........................................ 156 10.2.1 Data Acquisition................................ 158 10.2.2 Parameter Estimation................................................... 159 10.2.3 Results and Discussion......................................................... 161 10.3 Case Study-2: The #MeToo Social Movement ..................... 163 10.3.1 Data Acquisition............................................................ 164 10.3.2 Parameter Estimation................................................... 165 10.3.3 Results and Discussion.................................................... 165 10.4 Case Study-3: 2018 Golden Globe Awards.................................■ 167 10.4.1 Data Acquisition............................................................. 168 10.4.2
Parameter Estimation.................................................... 170 10.4.3 Results and Discussion.................................................... 173 10.5 Case Study-4: Viral Internet Debates ................................... 173 10.5.1 Data Acquisition............................................................. 174 10.5.2 Parameter Estimation.................................................... 176 10.5.3 Results and Discussion......................................................... 177 10.6 Exercises .................................................................................... 179 Ш Control Methods For Information Spread 11 Control Basics 11.1 11.2 11.3 11.4 11.5 181 183 Introduction .............................................................................. 183 Open-loop and Closed-loop Control Systems ........................ 184 SISO and MIMO ControlSystems............................................ 185 Continuous-time and Discrete-time Control Systems............ 186 Control System Design ...............................................................187 12 Control Methods 189 12.1 State Variable Feedback Controller ...................................... 190 12.1.1 Full-state Feedback Control Design.............................. 190 12.1.2 Observer Design.................................................................. 191 12.1.3 Full-state FeedbackController and Observer................. 192 12.2 PID Controller.......................................................................... 192 12.3 Optimal
Control....................................................................... 193 12.3.1 Performance Measure ................................................... 194
Contents 12.3.2 Dynamic Programming and Principle of Optimality . 195 12.3.3 Pontryagin’s Minimization Principle........................... 19(i 12.3.4 Illustrative Example...........................................................197 12.4 Exercises ........................................................................................ 201 13 Information Spread and Control 13.1 13.2 13.3 13.4 14 Control Application 1: Advertisements and Social Crazes 14.1 14.2 14.3 14.4 14.5 211 Scenario Description...................................................................... 211 Problem Formulation .............................................................. 212 Dynamic Programming Approach ......................................... 213 Pontryagin s Approach ........................................................... 214 Numerical Solution and Discussion......................................... 215 15 Control Application 2: Stopping a Fake News Outbreak 15.1 15.2 15.3 15.4 203 Controlling Socio-technical Systems ...................................... 203 The Control Action and Social Media Systems .......................... 207 Optimal Control and Social Media......................................... 208 Exercises ................................................................................... 209 221 Scenario Description...................................................................... 221 Problem Formulation .............................................................. 222 Pontryagin’s Approach ........................................................... 224 Numerical
Solution and Discussion......................................... 225 16 Concluding Thoughts 16.1 What Have We Learned? ........................................................ 16.2 But Now What?....................................................................... 16.3 The Future and Beyond........................................................... 233 233 235 236 Bibliography 237 Index 245
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 pptimal 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.
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| language | English |
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| spellingShingle | Muhlmeyer, Michael Agarwal, Shaurya Information spread in a social media age modeling and control Social Media (DE-588)4639271-3 gnd Information (DE-588)4026899-8 gnd Soziomarketing (DE-588)4116549-4 gnd Verbreitung (DE-588)4187586-2 gnd Mathematische Modellierung (DE-588)7651795-0 gnd |
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| title | Information spread in a social media age modeling and control |
| title_auth | Information spread in a social media age modeling and control |
| title_exact_search | Information spread in a social media age modeling and control |
| title_full | Information spread in a social media age modeling and control Michael Muhlmeyer, Shaurya Agarwal |
| title_fullStr | Information spread in a social media age modeling and control Michael Muhlmeyer, Shaurya Agarwal |
| title_full_unstemmed | Information spread in a social media age modeling and control Michael Muhlmeyer, Shaurya Agarwal |
| title_short | Information spread in a social media age |
| title_sort | information spread in a social media age modeling and control |
| title_sub | modeling and control |
| topic | Social Media (DE-588)4639271-3 gnd Information (DE-588)4026899-8 gnd Soziomarketing (DE-588)4116549-4 gnd Verbreitung (DE-588)4187586-2 gnd Mathematische Modellierung (DE-588)7651795-0 gnd |
| topic_facet | Social Media Information Soziomarketing Verbreitung Mathematische Modellierung |
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