Table of Contents

Table of Content

Preface xi
Acknowledgments xv

1 Introduction 1

  • 1.1 What is Social Media Mining 1
  • 1.2 New Challenges for Mining 2
  • 1.3 Book Overview and Reader’s Guide 3
  • 1.4 Summary 6
  • 1.5 Bibliographic Notes 7
  • 1.6 Exercises 8

Part I Essentials

2 Graph Essentials 13

  • 2.1 Graph Basics 14
  • 2.2 Graph Representation 18
  • 2.3 Types of Graphs 20
  • 2.4 Connectivity in Graphs 22
  • 2.5 Special Graphs 26
  • 2.6 Graph Algorithms 31
  • 2.7 Summary 46
  • 2.8 Bibliographic Notes 47
  • 2.9 Exercises 48

3 Network Measures 51

  • 3.1 Centrality 52
  • 3.2 Transitivity and Reciprocity 64
  • 3.3 Balance and Status 69
  • 3.4 Similarity 71
  • 3.5 Summary 76
  • 3.6 Bibliographic Notes 77
  • 3.7 Exercises 78

4 Network Models 80

  • 4.1 Properties of Real-World Networks 80
  • 4.2 Random Graphs 84
  • 4.3 Small-World Model 93
  • 4.4 Preferential Attachment Model 97
  • 4.5 Summary 101
  • 4.6 Bibliographic Notes 102
  • 4.7 Exercises 103

5 Data Mining Essentials 105

  • 5.1 Data 106
  • 5.2 Data Preprocessing 111
  • 5.3 Data Mining Algorithms 113
  • 5.4 Supervised Learning 113
  • 5.5 Unsupervised Learning 127
  • 5.6 Summary 133
  • 5.7 Bibliographic Notes 134
  • 5.8 Exercises 135

Part II Communities and Interactions

6 Community Analysis 141

  • 6.1 Community Detection 144
  • 6.2 Community Evolution 161
  • 6.3 Community Evaluation 168
  • 6.4 Summary 174
  • 6.5 Bibliographic Notes 175
  • 6.6 Exercises 176

7 Information Diffusion in Social Media 179

  • 7.1 Herd Behavior 181
  • 7.2 Information Cascades 186
  • 7.3 Diffusion of Innovations 193
  • 7.4 Epidemics 200
  • 7.5 Summary 209
  • 7.6 Bibliographic Notes 210
  • 7.7 Exercises 212

Part III Applications

8 Influence and Homophily 217

  • 8.1 Measuring Assortativity 218
  • 8.2 Influence 225
  • 8.3 Homophily 234
  • 8.4 Distinguishing Influence and Homophily 236
  • 8.5 Summary 240
  • 8.6 Bibliographic Notes 241
  • 8.7 Exercises 242

9 Recommendation in Social Media 245

  • 9.1 Challenges 246
  • 9.2 Classical Recommendation Algorithms 247
  • 9.3 Recommendation Using Social Context 258
  • 9.4 Evaluating Recommendations 263
  • 9.5 Summary 267
  • 9.6 Bibliographic Notes 268
  • 9.7 Exercises 269

10 Behavior Analytics 271

  • 10.1 Individual Behavior 271
  • 10.2 Collective Behavior 283
  • 10.3 Summary 290
  • 10.4 Bibliographic Notes 291
  • 10.5 Exercises 292

Notes 295
Bibliography 299
Index 315

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